{"id":2905,"date":"2017-04-04T17:03:19","date_gmt":"2017-04-04T08:03:19","guid":{"rendered":"http:\/\/www.sie.ics.saitama-u.ac.jp\/?page_id=23"},"modified":"2023-07-05T18:35:33","modified_gmt":"2023-07-05T09:35:33","slug":"achievement","status":"publish","type":"page","link":"https:\/\/www.sie.ics.saitama-u.ac.jp\/index.php\/achievement\/","title":{"rendered":"\u7814\u7a76\u696d\u7e3e"},"content":{"rendered":"\n
\n
\n
\n

\u53d7\u8cde<\/strong><\/h2>\n\n\n\n

IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, Gold Paper Award<\/strong> (Best Paper Award), 2012<\/p>\n\n\n

\n\n\n\n

WSEAS International Conference on Multimedia Systems and Signal Processing, Best Paper Award<\/strong>, 2013<\/p>\n\n\n

\n\n\n\n

Journal of Signal Processing, Best Paper Award<\/strong>, 2013, 2015, 2016<\/p>\n\n\n

\n\n\n\n

IEEE International Symposium on Intelligent Signal Processing and Communication Systems, Best Paper Award<\/strong>, 2016<\/p>\n\n\n

\n\n\n\n

IEEE International Conference on Electrical, Computer and Communication Engineering, Best Paper Award<\/strong>, 2017<\/p>\n\n\n\n

\u8ad6\u6587<\/strong><\/h2>\n\n\n
<\/div>
<\/span>\u30af\u30ea\u30c3\u30af\u3067\u5c55\u958b<\/div>
M. A. Rahman, Y. Sugiura, T. Shimamura and H. Makinae, \u201cLP-Based Quality Improvement of Noisy Bone-Conducted Speech,\u201d IEEJ Trans. Electronics, Information and Systems, Vol.137, No.1, pp.197-198, 2017.<\/p>\n
\n

M. S. Hossain and T. Shimamura, \u201cLow-Complexity Null Subcarrier-Assisted OFDM PAPR Reduction with Improved BER,\u201d Journal of Signal Processing, Vol.21, No.1, pp.1-13, 2017.<\/p>\n

\n

M. S. Hossain and T. Shimamura, \u201cLow-Complexity Null Subcarrier-Assisted OFDM PAPR Reduction with Improved BER,\u201d IEEE Communications Letters, Vol. 20, No.11, pp.2249-2252, 2016.<\/p>\n

\n

M. S. Rahman and T. Shimamura, \u201cPitch Determination from Bone Conducted Speech,\u201d IEICE Transactions on Information and Systems, Vol. E99-D, No.1, pp.283-287, 2016. 1.<\/p>\n

\n

L. Liu and T. Shimamura, \u201cPitch-Synchronous Linear Prediction Analysis of High-Pitched Speech Using Weighted Short-Time Energy Function,\u201d Journal of Signal Processing, Vol.19, No.2, pp.55-66, 2015. 3.<\/p>\n

\n

P. K. Dhar and T. Shimamura, \u201cBlind SVD-Based Audio Watermarking Using Entropy and Log-Polar Transformation,\u201d Journal of Information Security and Applications, Vol.20, pp.74-83, 2015. 2.<\/p>\n

\n

P. K. Dhar and T. Shimamura, \u201cAudio Watermarking Based on Eigenvalue Decomposition ,\u201d IEICE Trans. Fundamentals, Vol.E97-A, No.12, pp.2658-2661, 2014. 12.<\/p>\n

\n

P. K. Dhar and T. Shimamura, \u201cAudio Watermarking in Transform Domain Based on Singular Value Decomposition and Cartesian-Polar Transformation,\u201d International Journal of Speech Technology, Vol.17, No.2, pp.133-144, 2014. 6.<\/p>\n

\n

A. Saha and T. Shimamura, \u201cNoise Spectrum Estimation Based on SNR Discrepancy for Speech Enhancement,\u201d IEICE Transactions on Information and Systems, Vol. E97-D, No.2, pp.373-377, 2014. 2.<\/p>\n

\n

T. Kaneko and T. Shimamura, \u201cNoise-Reduced Complex LPC Analysis for Formant Estimation of Noisy Speech,\u201d International Journal of Electronics and Electrical Engineering, Vol.2, No.2, pp.90-94, 2014. 2.<\/p>\n

\n

C. Yi and T. Shimamura, \u201cAn Improved Structure-Based Gaussian Variance Estimation Method for Noisy Images,\u201d Journal of Signal Processing, Vol.17, No.6, pp.299-305, 2013. 11.<\/p>\n

\n

L. Liu and T. Shimamura, \u201cA Noise Compensation LPC Method Based on Pitch Synchronous Analysis for Speech,\u201d Journal of Signal Processing, Vol.17, No.6, pp.283-292, 2013. 11.<\/p>\n

\n

P. K. Dhar and T. Shimamura, \u201cAudio Watermarking in Transform Domain Based on Singular value Decomposition and Cartesian-Polar Transformation,\u201d International Journal of Speech Technology, Vol.17, No.2, pp.133-144, 2013. 9.<\/p>\n

\n

P. K. Dhar and T. Shimamura, \u201cA DWT-DCT-Based Audio Watermarking Method Using Singular value Decomposition and Quantization,\u201d Journal of Signal Processing, Vol.17, No.3, pp.69-79, 2013. 5.<\/p>\n

\n

M. A. F. M. Rashidul Hasan, M. Shahidul Rahman and Tetsuya Shimamura, \u201cWindowless Autocorrelation Based Cepstrum Method for Pitch Extraction of Noisy Speech,\u201d Journal of Signal Processing, Vol.16, No.3, pp.231-239, 2012.<\/p>\n

\n

M. A. F. M. Rashidul Hasan and Tetsuya Shimamura, \u201cAn Efficient Pitch Estimation Method Using Windowless and Normalized Autocorrelation Functions in Noisy Environments,\u201d International Journal of Circuits, Systems and Signal Processing, Vol.6, Issue 3, pp.197-204, 2012.<\/p>\n

\n

C. Yi and T. Shimamura, \u201dAn Improved Maximum-Likelihood Estimation Algorithm for Blind Image Deconvolution Based on Noise Variance Estimation,\u201d Journal of Signal Processing, Vol.16, No.6, pp.629-635, 2012. 11.<\/p>\n

\n

A. Saha and T. Shimamura, \u201dPerceptually Motivated Bayesian Estimators with Generalized Gamma Distribution under Speech Presence Probability,\u201d International Journal of Circuits, Systems and Signal Processing, Issue 1, Vol.6, pp.105-112, 2012.<\/p>\n

\n

S. Sari and T. Shimamura, \u201dFrequency Domain Wiener Filer for Image Denoising : Derivation of a New Power Spectrum Estimation Method,\u201d Journal of Signal Processing, Vol.16, No.1, pp.79-85, 2012. 1.<\/p>\n

\n

A. Saha and T. Shimamura, \u201dSpeech Enhancement by Incorporating Speech Presence Probability Based on SNR Discrepancy,\u201d Journal of Signal Processing, Vol.16, No.1, pp.57-65, 2012. 1.<\/p>\n

\n

R. Yasmin, S. Oikawa, Y. Tsuda and T. Shimamura, \u201dAmplitude-Division-Based Parallel LMS Estimation Technique for Rapidly Time-Varying Channel,\u201d Journal of Signal Processing, Vol.15, No.5, pp.387-397, 2011. 9.<\/p>\n

\n

S. Sari and T. Shimamura, \u201dImage Restoration Based on Edgemap and Wiener Filter for Preserving Fine Details and Edges,\u201d International Journal of Circuits, Systems and Signal Processing, Issue.6, Vol.5, pp.618-626, 2011.<\/p>\n

\n

R. Yasmin and T. Shimamura, \u201dBlind Channel Equalization in Impulse Noise,\u201d International Journal of Communications, Issue 3, Vol.5, pp.132-140, 2011. 7.<\/p>\n

\n

M. L. R. Khan and T. Shimamura, \u201cTransform Domain Sato Algorithm for Blind Channel Equalization\u201d, Journal of Signal Processing, Vol.15, No.2, pp.123-131, 2011. 3.<\/p>\n

\n

J. Gamba, T. Shimamura, S. Kawasaki, M. Higuchi and H. Murakami, \u201cA Joint Iterative Estimation of Noise Variance and AR Parameters\u201d, International Journal of Information Sciences and Computer Engineering, Vol.2, No.1, pp.1-6, 2011.<\/p>\n

\n

M. L. R. Kahn, M. H. Wondimagegnehu and T. Shimamura, Blind Channel Equalization with Amplitude Banded Godard and Sato Algorithms, Journal of Communications, Vol.4, No.6, pp.388-395, 2009.<\/p>\n

\n

H. Furuya, S. Eda and T. Shimamura, \u201cImage Restoration via Wiener Filtering in the Frequency Domain\u201d, WSEAS Transactions on Signal Processing, Issue 2, Vol.5, pp.63-73\uff0c2009\uff0e2\uff0e<\/p>\n

\n

W. Xin, K. Kondo, K. Tateno, T. Konma and T. Shimamura, \u201cDiscrete Wavelet Based Keyframe Extraction Method from Motion Capture Data\u201d, International Journal of Asia Digital Art and Design, Vol.6, pp.11 – 18, 2007<\/p>\n

\n

M.S. Rahman and T. Shimamura, Linear Prediction Using Refined Autocorrelation Function, EURASIP Journal on Audio, Speech and Music Processing, Volume 2007, Article ID 45962, 9 Pages, 2007<\/p>\n

\n

H. Tanaka\uff0cY. Ohhashi and T. Shimamura\uff0cPerformance of Adaptive Nonlinear Predictor with Order Statistics in Impulsive Noise\uff0cWSEAS Transactions on Signal Processing\uff0cIssue 2, Vol.3, 2007. 2.<\/p>\n

\n

H.W. Mohammed and T. Shimamura\uff0cA Parallel Equalizer with LMS Adaptation in Discrete Cosine Transform Domain\uff0cWSEAS Transactions on Signal Processing\uff0cIssue 2, Vol.3, 2007. 2.<\/p>\n

\n

M.S. Rahman and T. Shimamura\uff0c Identification of ARMA Speech Models Using an Effective Representation of Voice Source\uff0c IEICE Transactions on Information and Systems\uff0cVol.E90-D\uff0c2007<\/p>\n

\n

H.W. Mohammed and T. Shimamura\uff0cComplementary and Phase Banded LMS Equalizers for Rapidly Time-Varying Channels\uff0c Journal of Signal Processing\uff0cVol.11\uff0cNo.1\uff0cpp.51-60, 2007\uff0e1\uff0e<\/p>\n

\n<\/div><\/div>\n\n\n\n

\u5b66\u5916\u767a\u8868\uff08\u56fd\u969b\u5b66\u4f1a\uff09<\/strong><\/h2>\n\n\n
<\/div>
<\/span>\u30af\u30ea\u30c3\u30af\u3067\u5c55\u958b<\/div>
M. Geng, Y. Sugiura and T. Shimamura, \u201cNoise Subtraction and Pitch Synchronous Addition for LPC Analysis of Noisy Speech,\u201d Proceeding of RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, 4 Pages, 2017. 3.<\/p>\n
\n

M. Hijikata, Y. Sugiura and T. Shimamura, \u201cMusical Noise Suppression for Spectral Subtraction Using Histogram of Power Spectrum,\u201d Proceeding of RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, 4 Pages, 2017. 3.<\/p>\n

\n

I. Sikder, P. K. Dhar and T. Shimamura, \u201cA Semi-Fragile Watermarking Method Using Slant Transform and LU Decomposition for Image Authentication,\u201d Proceedings of IEEE International Conference on Electrical, Computer and Communication Engineering, 2017.<\/p>\n

\n

S. Zhang, Y. Sugiura, T. Shimamura and H. Makinae, \u201cFundamental Frequency Estimation Combining Air-Conducted Speech with Bone-Conducted Speech in Noisy Enviroments,\u201d Proceedings of IEEE International Conference on Electrical, Computer and Communication Engineering, 2017.<\/p>\n

\n

T. Zhou, Y. Sugiura and T. Shimamura, \u201cIterative Extended Spectral Subtraction for Restoration from Image Degraded by White Noise,\u201d Proceedings of IEEE International Conference on Electrical, Computer and Communication Engineering, 2017.<\/p>\n

\n

M. Ogura, Y. Sugiura and T. Shimamura, \u201cSVD Based Audio Watermarking Using Angle-Quantization,\u201d Proceedings of IEEE International Conference on Electrical, Computer and Communication Engineering, 2017.<\/p>\n

\n

K. Mitani, Y. Sugiura and T. Shimamura, \u201cCross-Correlation Functions with Binary Signal Involving Phase Information for Speech Enhancement,\u201d Proceedings of IEEE International Symposium on Intelligent Signal Processing and Communication Systems, 5 Pages, 2016.<\/p>\n

\n

S. Asawa, Y. Sugiura and T. Shimamura, \u201cSpeech Envelope Estimation and Voiceless Consonant Restoration for Artificial Bandwidth Extension of Narrow Band Speech,\u201d Proceedings of IEEE International Symposium on Intelligent Signal Processing and Communication Systems, 6 Pages, 2016.<\/p>\n

\n

E. Ogawa, Y. Sugiura and T. Shimamura, \u201cNarrowband Interference Suppression with Symbol Interleaving for UWB Communication Systems,\u201d Proceedings of IEEE Asia Pacific Conference on Circuits and Systems, pp.172-175, 2016.<\/p>\n

\n

K. Ishiyama, Y. Sugiura and T. Shimamura, \u201cOptimized Three Scores Combination for Image Quality Assessment,\u201d Proceedings of IEEE Asia Pacific Conference on Circuits and Systems, pp.5-8, 2016.<\/p>\n

\n

H. Chu and T. Shimamura, \u201cA New PTS Method for OFDM Signals without Side Information Based on Constellation Reshaping,\u201d Proceedings of IEEE Annual Conference on Information Science and Systems, pp.222-227, 2016. 3.<\/p>\n

\n

Y. Iwai and T. Shimamura, \u201cSpeech Enhancement with Zero Replacement Signal at Low SNR,\u201d Proceedings of IEEE International Symposium on Intelligent Signal Processing and Communications Systems, pp.143-147, 2015. 11.<\/p>\n

\n

M. S. Hossain and T. Shimamura, \u201cPAPR Reduction of OFDM Through Pilot Shifting,\u201d Proceedings of IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, pp.179-184, 2015. 9.<\/p>\n

\n

E. Abe and T. Shimamura, \u201cSpeech Enhancement with p-th Power Amplitude Spectrum in Highly Noisy Environments,\u201d Proceedings of IEICE International Workshop on Smart Info-Media Systems in Asia, pp.90-93, 2015. 8.<\/p>\n

\n

E. Abe and T. Shimamura, \u201cUtilization of Exponentiated Amplitude Spectrum for Speech Enhancement in Highly Noisy Environments,\u201d Proceedings of IEEE Midwest Symposium on Circuits and Systems, 4 pages, 2015. 8.<\/p>\n

\n

T. Shimamura and F. Kato, \u201cCombination of Bone-Conducted Speech with Air-Conducted Speech Changing Cut-Off Frequency,\u201d Proceedings of WSEAS International Conference on Acoustics, Speech and Audio Processing, pp.142-147, 2015. 6.<\/p>\n

\n

K. Honma and T. Shimamura, \u201cEfficient Blind Modulation Detection Using Sub-optimum Maximum Likelihood Function in Multiple Antennas,\u201d Proceeding of RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, 2015. 3.<\/p>\n

\n

L. Liu and T. Shimamura, \u201cLinear Prediction Analysis of Crosscorrelation Sequence for Voiced Speech,\u201d Proceedings of APSIPA Annual Summit and Conference, pp.1-4, 2014. 12.<\/p>\n

\n

M. Toyoshima and T. Shimamura, \u201cPacket Loss Concealment for VoIP Based on Pitch Waveform Replication and Linear Predictive Coding,\u201d Proceedings of IEEE Asia Pacific Conference on Circuits and Systems, pp.89-92, 2014. 11.<\/p>\n

\n

Y. Iwai and T. Shimamura, \u201cFormant Frequency Estimation with Windowless Autocorrelation in the Presence of Noise,\u201d Proceedings of IEEE Asia Pacific Conference on Circuits and Systems, pp.81-84, 2014. 11.<\/p>\n

\n

P. K. Dhar and T. Shimamura, \u201cImage Watermarking in LWT Domain Based on Nonnegative Matrix Factorization and Singular Value Decomposition,\u201d Proceedings of IEEE International Forum on Strategic Technology, pp.144-147, 2014.10.<\/p>\n

\n

S. Jimaa, L. Weruaga, A. Sadiq, H. Alhammadi and T. Shimamura, \u201cA Fast Converging Improved NLMS Algorithm for Sparse System\u2019s Identification,\u201d Proceedings of International Symposium on Nonlinear Theory and Its Applications, pp676-679, 2014.9.<\/p>\n

\n

T. Arnantapunpong and T. Shimamura, \u201cDirection-of-Arrival Estimation for Smart Antenna Using MUSIC Algorithm with Data Extension,\u201d Proceedings of International Technical Conference on Circuits \/ Systems, Computers and Communications, pp.75-78, 2014. 6.<\/p>\n

\n

P.K.Dhar and T. Shimamura, \u201cA Blind SVD-Based Audio Watermarking Using Entropy and Log-Polar Transformation,\u201d Proceedings of IEEE International Symposium on Circuits and Systems, pp.125-128, 2014. 6.<\/p>\n

\n

N. Benamirouche, B. Boudraa, T. Shimamura and P.K. Dhar, \u201cImproved Packets Loss Concealment in Speech Coding by Data Hiding,\u201d Proceedings of IEEE International Conference on Advanced Technologies for Signal and Image Processing, pp.476-479, 2014. 3.<\/p>\n

\n

M. Shimozaki, C. Yi and T. Shimamura, A Performance Comparison of Some Image Denoising Methods,\u201d Proceeding of RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, 2014. 3.<\/p>\n

\n

S. Handa and T. Shimamura, High-Pitched Speech Analysis by System Identification Approach,\u201d Proceeding of RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, 2014. 3.<\/p>\n

\n

F. Kato and T. Shimamura, \u201cSpeech Enhancement with a Reversed Comb Filter in Non-Stationary Noise Environments,\u201d Proceeding of RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing, 2014. 3.<\/p>\n

\n

T. Kaneko and T. Shimamura, \u201cNoise-Reduced Complex LPC Analysis for Formant Estimation of Noisy Speech,\u201d Proceedings of International Conference on Advanced in Electronics Engineering, 5 pages, 2014. 2.<\/p>\n

\n

C. Yi and T. Shimamura, \u201cDifference Eigenvalue Based Gaussian Noise Variance Estimation for Images,\u201d Proceedings of WSEAS International Conference on Applied Computer Science, pp.27-33, 2014. 1.<\/p>\n

\n

T. Shimamura and T. Yokose, \u201cAR-Model-Based Data Extension to Improve the performance of MUSIC,\u201d Proceedings of IEEE International Symposium on Intelligent Signal Processing and Communication Systems, pp.458-461, 2013. 11.<\/p>\n

\n

K. Honma and T. Shimamura, \u201cConstellation Folding for Sub-Optimum Maximum-Likelihood Method in Blind Modulation Detection,\u201d Proceedings of IEEE International Symposium on Intelligent Signal Processing and Communication Systems, pp.103-107, 2013. 11.<\/p>\n

\n

M. S. Rahman and T. Shimamura, \u201cA Study on Amplitude Variation of Bone Conducted Speech Compared to Air Conducted Speech,\u201d Proceedings of APSIPA Annual Summit and Conference, 5 pages, 2013. 11.<\/p>\n

\n

K. Isono and T. Shimamura, \u201cExponetiated Combination of Tow Scores for Image Quality Assessment,\u201d Proceedings of IEEE Region 10 Conference, 4 pages, 2013. 10.<\/p>\n

\n

T. Shimamura and C. Abe, \u201cWhitening Poisson Noise on Images,\u201d Proceedings of IEICE International Workshop on Smart Info-Media Systems in Asia, pp.317-322, 2013. 10.<\/p>\n

\n

P. K. Dhar and T. Shimamura, \u201cEntropy-Based Audio Watermarking Using Singular Value Decomposition and Log-Polar Transform,\u201d Proceedings of IEEE Midwest Symposium on Circuits and Systems, pp.1224-1227, 2013. 8.<\/p>\n

\n

P. K. Dhar and T. Shimamura, \u201cAn SVD-Based Audio Watermarking Using Variable Embedding Strength and Exponential-Log Operations,\u201d Proceedings of IEEE International Conference on Informatics, Electronics and Vision, 6 pages, 2013.5.<\/p>\n

\n

S. Sari, H. Roslan and T. Shimamura, \u201cDenoising by Utilizing Mean Deviation of Image\u2019s Smooth Region,\u201d Proceedings of WSEAS International Conference on Multimedia Systems and Signal Processing, pp.194-198, 2013.4.<\/p>\n

\n

A. Saha, S. Ogata, Y. Mitsumori, M. Shahidur Rahman and T. Shimamura, \u201cSpeech Enhancement Using a Priori SNR: Dependency on Multitaper Spectrum Estimation,\u201d Proceedings of International Conference on Engineering, Research, Innovation and Education, pp.1-7, 2013. 1.<\/p>\n

\n

C. Yi and T. Shimamura, \u201cImproved Structure-Based Noise Variance Estimation for Noisy Images,\u201d Proceedings of IEEE International Symposium on Signal Processing and Information Technology, pp.1-5, 2012. 12.<\/p>\n

\n

L. Liu and T. Shimamura, \u201cPink Noise Whitening Method for Pitch Synchronous LPC Analysis,\u201d Proceedings of APSIPA Annual Summit and Conference, pp.1-6, 2012. 12.<\/p>\n

\n

G. Hirano and T. Shimamura, \u201cA Modified IPNLMS Algorithm Using System Sparseness,\u201d Proceedings of IEEE International Symposium on Intelligent Signal Processing and Communication Systems, pp.876-879, 2012. 11.<\/p>\n

\n

T. Kato and T. Shimamura, \u201cConsonant Behavior of Bone Conducted Speech in Japanese,\u201d Proceedings of IEEE International Symposium on Intelligent Signal Processing and Communication Systems, pp.485-488, 2012. 11.<\/p>\n

\n

S. Jimaa, S. Alaraji, A. Al-kabi and T. Shimamura, \u201cImpulse Noise Reduction Using Adaptive Receiver Structure Technique,\u201d Proceedings of IEEE International Conference on Signal Processing, pp.119-122, 2012. 10.<\/p>\n

\n

P. K. Dhar and T. Shimamura, \u201cAudio Watermarking in Transform Domain Based on Singular Value Decomposition and Quantization,\u201d Proceedings of IEEE Asia-Pacific Conference on Communications, pp.516-521, 2012.10.<\/p>\n

\n

S. Sari, H. Roslan and T. Shimamura, \u201dNoise Estimation by Utilizing Mean Deviation of Smooth Region in Noisy Image,\u201d Proceedings of IEEE International Conference on Computational Intelligence, Modelling and Simulation, pp.1-5, 2012\uff0e9\uff0e<\/p>\n

\n

A. Iwagami and T. Shimamura, \u201cNoise Cancellation Process for Automatic Train Protection (ATP), \u201c Proceedings of International Symposium on Speed-up, Safety and Service Technology for Railway and MAGLEV Systems, pp.1-7, 2012. 9.<\/p>\n

\n

A. Saha and T. Shimamura, \u201dSpeech Enhancement with Bivariate Gamma Model,\u201d Proceedings of INTERSPEECH, pp.1-4, 2012. 9.<\/p>\n

\n

T. Shimamura and A. Matsukawa, \u201cTime-Varying Noise Estimation Using Only Current Frame for Spectral Subtraction,\u201d Proceedings of WSEAS International Conference on Signal Processing, Computational Geometry and Artificial Vision, pp.80-83, 2012. 8\uff0e<\/p>\n

\n

S. Suhaila and T. Shimamura, \u201dFast Wiener Filter-Based Denoising for Fine Details and Edges Preservation in the Blind Condition,\u201d Proceedings of IEEE Midwest Symposium on Circuits and Systems, pp.498-501, 2012. 8.<\/p>\n

\n

P. K. Dhar and T. Shimamura, \u201cAn Audio Watermarking Scheme Using Discrete Fourier Transformation and Singular Value Decomposition,\u201d Proceedings of IEEE International Conference on Telecommunications and Signal Processing, pp.789-794, 2012.7.<\/p>\n

\n

D. Shimizu, T. T. Shimamura. Wakutsu and A. Sugawara, \u201dHarmonics Estimation for Reducing Return Current Noise in Automatic Train Control Systems,\u201d Proceedings of RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing\uff0cpp.647-650\uff0c2012. 3\uff0e<\/p>\n

\n

T. Kina and T. Shimamura, \u201dFundamental Frequency Extraction of Speech in Time-Varying Noise,\u201d Proceedings of RISP International Workshop on Nonlinear Circuits, Communications and Signal Processing\uff0cpp.325-328\uff0c2012. 3\uff0e<\/p>\n

\n

M. A. F. M. Rashidul Hasan and T. Shimamura, \u201dA Fundamental Frequency Extraction Method Based on Windowless and Normalized Autocorrelation Functions,\u201d Proceedings of WSEAS International Conference on Circuits, Systems, Signal and Telecommunications, pp.305-309, 2012. 1.<\/p>\n

\n

M. Narita and T. Shimamura, \u201dExponentiated Enhancement for Fundamental Frequency Extraction of Noisy Speech,\u201d Proceeding of IEEE International Symposium on Signal Processing and Information Technology, pp.342-346, 2011. 12.<\/p>\n

\n

C. Yi and T. Shimamura, \u201dA Blind Image Deconvolution Method Based on Noise Variance Estimation and Blur Type Reorganization,\u201d Proceedings of IEEE International Symposium on Intelligent Signal Processing and Communication Systems, PID235, 2011\uff0e12\uff0e<\/p>\n

\n

A. Saha and T. Shimamura, \u201dGeneralized Gamma Distributed Bayesian Estimator under Speech Presence Probability,\u201d Proceedings of WSEAS International Conference on Applied Computer Sciences, pp.118-123, 2011. 10.<\/p>\n

\n

A. Saha and T. Shimamura, \u201dSpeech Enhancement Using Masking Properties in Adverse Environments,\u201d Proceedings of INTERSPEECH, pp.1213-1216, 2011. 8.<\/p>\n

\n

A. Saha and T. Shimamura, \u201dWeighted Log-Spectral Amplitude Estimation with Generalized Gamma Distribution under Speech Presence Probability,\u201d Proceedings of EURASIP Signal Processing and Applied Mathematics for Electronics and Communications Workshop, pp.37-40, 2011. 8.<\/p>\n

\n

M. S. Rahman, A. Saha and T. Shimamura, \u201dLow-Frequency Band Noise Suppression Using Bone Conducted Speech,\u201d Proceeding of IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, pp.520-525, 2011. 8.<\/p>\n

\n

M. S. Rahman and T. Shimamura, \u201dIntelligibility Enhancement of Bone Conducted Speech by an Analysis-Synthesis Method,\u201d Proceedings of IEEE Midwest Symposium on Circuits and Systems, pp.1-4, 2011. 8.<\/p>\n

\n

S. Sari and T. Shimamura, \u201dEdgemap-Based Wiener Filtering for Preserving Image Fine Details and Edges,\u201d Proceedings of WSEAS International Conference on Systems, pp.264-269\uff0c2011\uff0e7\uff0e<\/p>\n

\n

T. Shimamura, A. Saha, M. Mori, Y. Ogawa and M. Sakai, \u201dSpectral Subtraction for Rain Clutter Suppression,\u201d Proceedings of IEICE International Conference on Circuits \/ Systems, Computers and Communications, pp.1221-1223, 2011. 6.<\/p>\n

\n

K. Osa, M. S. Rahman and T. Shimamura, \u201dSpeech Enhancement Using Comb Filter Designed from Bone Conducted Speech,\u201d Proceedings of IEICE International Conference on Circuits \/ Systems, Computers and Communications, pp.271-274, 2011. 6.<\/p>\n

\n

R. Yasmin and T. Shimamura, \u201dImpulse Noise Suppression in Blind Channel Equalization,\u201d Proceedings of WSEAS International Conference on Signal Processing, pp.194-200, 2011. 5\uff0e<\/p>\n

\n

A. Matsukawa and T. Shimamura, \u201cNoise Estimation Using Only Current Frame of Speech for Spectral Subtraction\u201d, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.425-428\uff0c2011. 3\uff0e<\/p>\n

\n

L. Liu and T. Shimamura, \u201cNoise Reduction Based on Pitch Synchronous Addition and Subtraction for LPC Analysis\u201d, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.348-351\uff0c2011. 3\uff0e<\/p>\n

\n

T. Yokose and T. Shimamura, \u201cPerformance Improvement of MUSIC by AR Model Based Data Extension\u201d, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.276-279\uff0c2011. 3\uff0e<\/p>\n

\n

S. Motegi and T. Shimamura, \u201cExtended Fundamental Frequency Extraction Using Exponentiated Amplitude Spectrum with Band-Limitation\u201d, Proceedings of IEEE International Conference on Signal Acquisition and Processing, pp.V1-168-V1-172\uff0c2011\uff0e2\uff0e<\/p>\n

\n

C. Abe and T. Shimamura, \u201cIterative Edge-Preserving Adaptive Wiener Filter for Image Denoising\u201d, Proceedings of IEEE International Conference on Signal Acquisition and Processing, pp.V1-168-V1-172\uff0c2011\uff0e2\uff0e<\/p>\n

\n

M. A. F. M. Rashidul Hasan, M. Shahidur Rahman and T. Shimamura, \u201cPitch Determination Using Windowless Autocorrelation Based Cepstrum Method\u201d, Proceedings of APSIPA Annual Summit and Conference 2010, pp.514-517, 2010. 12.<\/p>\n

\n

S. A. Jimaa and T. Shimamura, \u201cConvergence Evaluation of a Random Step-Size NLMS Adaptive Algorithm in System Identification\u201d, Proceedings of IEEE International Conference on Signal Processing, pp.135-138\uff0c2010\uff0e10\uff0e<\/p>\n

\n

T. Akasaka and T. Shimamura, \u201cNoise Estimation Based on Series Expansion of Orthogonal Functions\u201d, Proceedings of IEEE International Conference on Signal Processing, pp.115-118\uff0c2010\uff0e10\uff0e<\/p>\n

\n

R. Yasmin and T. Shimamura, \u201cTime-Varying Channel Estimation Using Amplitude-Division Based Parallel NLMS Technique\u201d, Proceedings of IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, pp.580-585\uff0c2010\uff0e10\uff0e<\/p>\n

\n

T. Shimamura and N. N. Dinh, \u201cAutocorrelation and Double Autocorrelation Representations for a Noisy Word Recognition System\u201d, Proceedings of INTERSPEECH 2010, pp.1712-1715, 2010\uff0e9\uff0e<\/p>\n

\n

M. S. Rahman and T. Shimamura, \u201cPitch Determination Using Autocorrelation Function in Spectral Domain\u201d, Proceedings of INTERSPEECH 2010, pp.653-656, 2010\uff0e9\uff0e<\/p>\n

\n

M. S. Rahman and T. Shimamura, \u201cPitch Characteristics of Bone Conducted Speech,\u201d Proceeding of European Signal Processing Conference (EUSIPCO), pp. 795-798, 2010. 8.<\/p>\n

\n

N. Yamasaki and T. Shimamura, \u201cAccuracy Improvement of Speaker Authentication in Noisy Environments Using Bone-Conducted Speech\u201d, Proceedings of IEEE International Midwest Symposium on Circuits and Systems, pp.197-200, 2010\uff0e8\uff0e<\/p>\n

\n

R. Yasmin and T. Shimamura, \u201cTracking by Nonuniform Amplitude Division Based LMS Algorithm for Time Varying Channels\u201d, Proceedings of IEEE International Symposium on Circuits and Systems, pp.2852-2855, 2010\uff0e5\uff0e<\/p>\n

\n

S. Suhaila and T. Shimamura, \u201cA Thresholding-Based Image Denoising Method\u201d, Proceedings of World Academy of Science and Technology, Vol.65, pp.911-916, 2010. 5\uff0e<\/p>\n

\n

K. Tashiro and T. Shimamura, A Lattice Based Fast Adaptive Algorithm, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing, pp.624-627 (2010).<\/p>\n

\n

T. Arnantapunpong, T. Shimamura and S. A. Jimaa, A New Variable Step Size for Normalized LMS Algorithm, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing, pp.584-587 (2010).<\/p>\n

\n

H. Takekawa, T. Shimamura and S. Irie, Digital Notch Filter for Noise Reduction in Automatic Train Control System, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing, pp.536-539 (2010).<\/p>\n

\n

C. Tiengwattanatum and T. Shimamura, Utilization of Adaptive Line Enhancement and Noise Compensation for Time Delay Estimation, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing, pp.524-527 (2010).<\/p>\n

\n

A. Saha and T. Shimamura, Noise Spectrum Estimation Based on Optimum Smoothing for Robust Speech Enhancement, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing, pp.293-296 (2010).<\/p>\n

\n

S. Suhaila and T. Shimamura, Power Spectrum Estimation Method for Image Denoising by Frequency Domain Wiener Filter, Proceedings of IEEE International Conference on Computer and Automation Engineering, pp.608-612 (2010).<\/p>\n

\n

S. A. Jimaa, A. Al-Simiri, R. M. Shubair and T. Shimamura, Convergence Evaluation of Variable Step-Size NLMS Algorithms in Adaptive Channel Equalization, Proceedings of IEEE International Symposium on Signal Processing and Information Technology, pp.145-150 (2009).<\/p>\n

\n

B. D. Dufera and T. Shimamura, Reverberated Speech Enhancement Using Neural Networks, Proceedings of IEEE International Symposium on Intelligent Signal Processing and Communication Systems, pp.441-444 (2009).<\/p>\n

\n

T. Shimamura, \u201cEqualization of Time-Variant Communications Channels via Adaptive AR Prefiltering\u201d, Proceedings of WRI World Congress on Computer Science and Information Engineering\uff0cpp.327-331 , 2009. 3\uff0e<\/p>\n

\n

N. Nakamura, T. Ikeda and T. Shimamura, \u201cTime Delay Estimation of Arrival and Spectrum Subtraction for Acoustic Dual-Microphone Systems\u201d, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.165-168\uff0c2009. 3\uff0e<\/p>\n

\n

K. Tashiro and T. Shimamura, \u201cDual Adaptive Pre-Whitening Filters for LMS Algorithm\u201d, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.1-4\uff0c2009. 3\uff0e<\/p>\n

\n

H. Furuya, S. Eda and T. Shimamura, \u201cImage Restoration via Wiener Filtering with Improved Noise Estimation\u201d, Proceedings of WSEAS International Conference on Signal Processing, Robotics and Automation, pp.315-320\uff0c2009\uff0e2\uff0e<\/p>\n

\n

M.L.R. Khan, M.H. Wondimagegnehu and T. Shimamura, \u201cAmplitude Banded Technique and Parallel Structure for Godard and Sato Algorithms of Blind Channel Equalization\u201d, Proceedings of International Conference on Computer and Information Technology, pp.768-772 , 2008\uff0e12\uff0e<\/p>\n

\n

B. Derebssa and T. Shimamura, \u201cHigh Pitch Source Isolation Using Complex Cepstrum in the Autocorrelation Domain\u201d, Proceedings of IEEE Asia Pacific Conference on Circuits and Systems, pp.1284-1287, 2008\uff0e11\uff0e<\/p>\n

\n

H. Takekawa, T. Shimamura and S. Jimaa, \u201cAn Efficient and Effective Variable Step Size NLMS Algorithm\u201d, Proceedings of Asilomar Conference on Signals, Systems and Computers, pp.1640-1643\uff0c2008\uff0e10\uff0e<\/p>\n

\n

C. Tiengwattanatum, N. Nakamura and T. Shimamura, \u201cAdaptive Line Enhancer for Time Delay Estimation of Ultrasonic Echoes\u201d, Proceedings of International Symposium on Communications and Information Technologies\uff0cpp.368-371, 2008. 10\uff0e<\/p>\n

\n

T. Shimamura, S. Oikawa S and Y. Tsuda, \u201cAmplitude-Division Parallel LMS Estimator\u201d, Proceedings of IEEE International Midwest Symposium on Circuits and Systems, pp.950-953, 2008\uff0e8\uff0e<\/p>\n

\n

S. Jimaa, T. Shimamura and H. Takekawa, \u201cConvergence Evaluation of a Variable Step-Size LMSE Adaptive Switching Algorithm\u201d, Proceedings of IEEE International Networking and Communications Conference, pp. 23-26\uff0c2008\uff0e5\uff0e<\/p>\n

\n

T. Sugiyama, T. Shimamura and H. Yashima, \u201cQuality Improvement of Bone-Conducted Speech Using Linear Prediction Analysis Filter\u201d, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.291-294 , 2008. 3\uff0e<\/p>\n

\n

S. Iijima and T. Shimamura, \u201cBone-Conducted Speech for Speaker Verification\u201d, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.172-175 , 2008. 3\uff0e<\/p>\n

\n

N. Nakamura and T. Shimamura, \u201cIterative Cross-Correlation Method for Time Delay Estimation\u201d, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.387-390 , 2008. 3\uff0e<\/p>\n

\n

T. Shimamura, S. Eda, T. Ito, Y. Kuwano and Y. Takahashi, Wavelet Based Denoising for Images Degraded by Poisson Noise, Proceedings of IASTED International Conference on Biomedical Engineering, pp.436-440\uff0c2008\uff0e2\uff0e<\/p>\n

\n

W. Xin, K. Kondo, K. Tateno, T. Konma and T. Shimamura, \u201cDiscrete Wavelet Based Keyframe Extraction Method from Motion Capture Data\u201d, Proceedings of NICOGRAPH, 2007.<\/p>\n

\n

M.L.R. Khan, H.W. Mohammed and T. Shimamura, \u201cAmplitude Banded Sato Algorithm for Blind Channel Equalization\u201d, Proceedings of IEEE International Conference on Signal Processing and Communications, pp.1463-1466, 2007\uff0e11\uff0e<\/p>\n

\n

S. Eda and T. Shimamura, \u201cImage Denoising for Poisson Noise by Pixel Values Based Division and Wavelet Shrinkage\u201d, Proceedings of International Symposium on Nonlinear Theory and Its Applications, pp.441-444 , 2007\uff0e9\uff0e<\/p>\n

\n

T. Shimamura, \u201cEqualization with Amplitude Banded LMS Adaptation for Stationary Channels\u201d, Proceedings of IASTED International Conference on Signal and Image Processing, 576-205\uff0c2007\uff0e8\uff0e<\/p>\n

\n

T. Shimamura, \u201cPerformance of the Amplitude Banded LMS Equalizer on Stationary Channels\u201d, Proceedings of IEEE International Workshop on Nonlinear Dynamics of Electronic Systems, pp. 289-292\uff0c2007\uff0e7\uff0e<\/p>\n

\n

K. Kamata, K. Yamashita, T. Shimamura and T. Furukawa, Restoration of Bone-Conducted Speech with the Wiener Filter and Long-Term Spectra, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.583-586, 2007. 3\uff0e<\/p>\n

\n

C. Tiengwattanatum, H.W. Mohammed and T. Shimamura, Magnitude Spectral Subtraction with DFTLMS Algorithm for Adaptive Line Enhancer, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.213-216, 2007. 3\uff0e<\/p>\n

\n

N. Nakamura and T. Shimamura\uff0cIndirect Cross-Correlation Method for Time Delay Estimation, Proceedings of RISP International Workshop on Nonlinear Circuits and Signal Processing\uff0cpp.74-77, 2007. 3.<\/p>\n

\n

H. Tanaka, Y. Ohhashi and T. Shimamura, Adaptive Non-Linear Prediction with Order Statistics for Speech in Impulsive Noise, Proceedings on WSEAS International Conference on Circuits, Systems, Signal and Telecommunications, pp.125-129, 2007. 1.<\/p>\n

\n

H.W. Mohammed and T. Shimamura, Discrete Cosine Transform Domain Parallel LMS Equalizer, Proceedings on WSEAS International Conference on Circuits, Systems, Signal and Telecommunications, pp.119-124, 2007. 1.<\/p>\n

\n<\/div><\/div>\n\n\n\n

\u8457\u66f8<\/strong><\/h2>\n\n\n\n

\u6c60\u539f\u96c5\u7ae0\uff0c\u5cf6\u6751\u5fb9\u4e5f<\/strong>\uff0c\u771f\u7530\u5e78\u4fca\uff0c2004\uff0cMATLAB\u30de\u30eb\u30c1\u30e1\u30c7\u30a3\u30a2\u4fe1\u53f7\u51e6\u7406\u3008\u4e0b\u3009\u97f3\u58f0\u30fb\u753b\u50cf\u30fb\u901a\u4fe1\uff0c\u57f9\u98a8\u9928<\/p>\n\n\n

\n\n\n\n

\u6c60\u539f\u96c5\u7ae0\uff0c\u5cf6\u6751\u5fb9\u4e5f<\/strong>\uff0c2004\uff0cMATLAB\u30de\u30eb\u30c1\u30e1\u30c7\u30a3\u30a2\u4fe1\u53f7\u51e6\u7406\u3008\u4e0a\u3009\u30c7\u30a3\u30b8\u30bf\u30eb\u4fe1\u53f7\u51e6\u7406\u306e\u57fa\u790e\uff0c\u57f9\u98a8\u9928<\/span><\/p>\n\n\n

\n\n\n\n

\u9ad8\u6a4b\u9032\u4e00\uff0c\u5cf6\u6751\u5fb9\u4e5f<\/strong>\uff0c2001\uff0c\u4e00\u6b21\u5143\u30c7\u30a3\u30b8\u30bf\u30eb\u4fe1\u53f7\u51e6\u7406\u306e\u57fa\u790e (\u96fb\u6c17\u30fb\u96fb\u5b50\u30fb\u60c5\u5831\u5de5\u5b66\u7cfb\u30c6\u30ad\u30b9\u30c8\u30b7\u30ea\u30fc\u30ba)\uff0c\u57f9\u98a8\u9928<\/p>\n\n\n\n

\u5b66\u4f4d\u8ad6\u6587<\/strong><\/h2>\n\n\n\n

\u5b66\u58eb\u8ad6\u6587<\/strong><\/p>\n\n\n\n\n\n\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t
2024\u5e74\u5ea6<\/td>\u9db4\u8cc0 \u5927<\/td>\u751f\u6210\u30e2\u30c7\u30eb\u3092\u7528\u3044\u305f\u4f4e\u7dda\u91cfCT\u753b\u50cf\u306e\u30ce\u30a4\u30ba\u9664\u53bb\u306b\u95a2\u3059\u308b\u7814\u7a76<\/a><\/td><\/td>\n<\/tr>\n
\u5927\u6cbc\u512a\u5e0c\u4eba<\/td>StereoLCM\uff1aLCM\u3092\u7528\u3044\u305f\u30b9\u30c6\u30ec\u30aa\u753b\u50cf\u751f\u6210\u306e\u9ad8\u901f\u5316<\/a><\/td><\/td>\n<\/tr>\n
\u4eba\u898b\u4e00\u4e5f<\/td>\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u30d5\u30a3\u30fc\u30c9\u30d0\u30c3\u30af\u578bANC\u306e\u8efd\u91cf\u5316<\/a><\/td><\/td>\n<\/tr>\n
\u85c1\u8c37\u53cb\u5e0c<\/td>\u97f3\u58f0\u5408\u6210\u306b\u304a\u3051\u308b\u97f3\u97ff\u7279\u5fb4\u91cf\u30a8\u30f3\u30b3\u30fc\u30c0\u306e\u91cd\u8981\u6027\u306e\u8a55\u4fa1<\/a><\/td><\/td>\n<\/tr>\n
\u534a\u6fa4\u606d\u4ecb<\/td>\u81ea\u5df1\u6559\u5e2b\u3042\u308a\u5b66\u7fd2\u306b\u3088\u308b\u672a\u77e5\u306e\u97f3\u58f0\u30c7\u30fc\u30bf\u306b\u5bfe\u3059\u308b\u97f3\u58f0\u5f37\u8abf\u6027\u80fd\u306e\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
2023\u5e74\u5ea6<\/td>\u5927\u6fa4\u5f18\u660e<\/td>\u30b9\u30d1\u30fc\u30b9\u4fe1\u53f7\u51e6\u7406\u3068\u30b3\u30b5\u30a4\u30f3\u985e\u4f3c\u5ea6\u3092\u7528\u3044\u305f\u548c\u97f3\u540d\u63a8\u5b9a<\/a><\/td><\/td>\n<\/tr>\n
\u9234\u6728\u7693\u592a<\/td>\u5de5\u5834\u9a12\u97f3\u306b\u7279\u5316\u3057\u305f\u8d85\u8efd\u91cf\u97f3\u58f0\u5f37\u8abf\u30b7\u30b9\u30c6\u30e0\u306e\u63d0\u6848<\/a><\/td><\/td>\n<\/tr>\n
\u4ef2\u91ce\u5929\u771f<\/td>\u990a\u8c5a\u74b0\u5883\u4e0b\u306b\u304a\u3051\u308b\u5b50\u8c5a\u306e\u9cf4\u304d\u58f0\u306b\u95a2\u3059\u308b\u97f3\u97ff\u7279\u5fb4\u91cf\u306e\u62bd\u51fa<\/a><\/td><\/td>\n<\/tr>\n
\u6ed1\u5ddd\u7fd4\u4ecb<\/td>\u5468\u6ce2\u6570\u9818\u57df\u80fd\u52d5\u9a12\u97f3\u5236\u5fa1\u306e\u6d88\u97f3\u6027\u80fd\u306e\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
\u7fbd\u7530\u84bc\u751f<\/td>\u5468\u6ce2\u6570\u9818\u57df\u306b\u304a\u3051\u308b\u80fd\u52d5\u9a12\u97f3\u5236\u5fa1\u306e\u5b9f\u6a5f\u5b9f\u88c5<\/a><\/td><\/td>\n<\/tr>\n
\u76ca\u5b50\u9678<\/td>Pixel Shuffle\u3068FP16\u3092\u7528\u3044\u305f\u52d5\u753b\u96d1\u97f3\u9664\u53bb\u6cd5\u306e\u9ad8\u901f\u5316<\/a><\/td><\/td>\n<\/tr>\n
2022\u5e74\u5ea6<\/td>\u539f\u7530\u96bc\u592a\u6717<\/td>\u30d1\u30bf\u30fc\u30f3\u60c5\u5831\u306e\u7279\u5fb4\u306b\u57fa\u3065\u3044\u305f\u4f34\u594f\u751f\u6210\u624b\u6cd5\u306e\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
\u91ce\u53e3\u51cc\u6c70<\/td>\u72ed\u5e2f\u57df\u9a12\u97f3\u5236\u5fa1\u306e\u305f\u3081\u306e\u5468\u6ce2\u6570\u9818\u57df\u3092\u7528\u3044\u305f\u30d5\u30a3\u30fc\u30c9\u30d0\u30c3\u30af\u578b\u80fd\u52d5\u9a12\u97f3\u5236\u5fa1<\/a><\/td><\/td>\n<\/tr>\n
\u5409\u826f\u9752\u7a7a<\/td>\u97f3\u58f0\u306b\u3088\u308b\u611f\u60c5\u63a8\u5b9a\u306b\u6700\u9069\u306a\u7279\u5fb4\u91cf\u306e\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
\u83ca\u6c60\u967d\u9999<\/td>\u6b21\u4e16\u4ee3\u81ea\u52d5\u8eca\u306e\u63a5\u8fd1\u901a\u5831\u97f3\u306b\u5bfe\u3059\u308b\u5370\u8c61\u306e\u8981\u56e0\u306b\u95a2\u3059\u308b\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
\u5317\u6761\u62d3\u5df3<\/td>\u548c\u97f3\u9032\u884c\u306e\u51fa\u73fe\u78ba\u7387\u3092\u8003\u616e\u3057\u305f\u548c\u97f3\u540d\u63a8\u5b9a\u624b\u6cd5\u306e\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
\u8239\u6a4b\u5c1a\u5c06<\/td>\u72ec\u7acb\u6210\u5206\u5206\u6790\u3092\u7528\u3044\u305f\u81ea\u52d5\u5909\u8abf\u5206\u985e\u5668\u306e\u7cbe\u5ea6\u5411\u4e0a<\/a><\/td><\/td>\n<\/tr>\n
2021\u5e74\u5ea6<\/td>\u516b\u5e61\u5bff\u5f25<\/td>\u52a0\u5de5\u6c17\u5c0e\u97f3\u8074\u53d6\u306b\u3088\u308b\u81ea\u5df1\u8074\u53d6\u97f3\u3068\u6c17\u5c0e\u97f3\u9593\u306e\u5dee\u7570\u306e\u4f4e\u6e1b<\/a><\/td><\/td>\n<\/tr>\n
\u5bae\u672c\u5468<\/td>AMeDAS\u30c7\u30fc\u30bf\u3092\u5229\u7528\u3057\u305f\u9069\u5fdc\u5909\u8abf\u65b9\u5f0f\u30fb\u7b26\u53f7\u5316\u7387\u9078\u629e\u306b\u3088\u308b\u9ad8\u52b9\u7387\u885b\u661f\u901a\u4fe1<\/a><\/td><\/td>\n<\/tr>\n
\u7be0\u7530\u958b\u6597<\/td>\u30b9\u30d1\u30fc\u30b9\u901a\u4fe1\u8def\u306b\u5bfe\u3059\u308b\u30d6\u30e9\u30a4\u30f3\u30c9\u63a8\u5b9a\u624b\u6cd5\u306e\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
\u4e2d\u91ce\u6e21\u99ff<\/td>\u632f\u5e45\u5909\u52d5\u97f3\u306b\u304a\u3051\u308b\u632f\u5e45\u5305\u7d61\u306e\u5f62\u72b6\u3068\u5909\u52d5\u611f\u306e\u95a2\u4fc2<\/a><\/td><\/td>\n<\/tr>\n
\u843d\u5408\u4eae<\/td>\u30b0\u30e9\u30d5\u4fe1\u53f7\u51e6\u7406\u3092\u7528\u3044\u305f\u30a8\u30c3\u30b8\u753b\u50cf\u306b\u304a\u3051\u308b\u7279\u5fb4\u91cf\u62bd\u51fa<\/a><\/td><\/td>\n<\/tr>\n
\u9577\u5cf6\u305b\u308a\u3042<\/td>Transformer\u3092\u7528\u3044\u305f\u753b\u50cf\u4e2d\u306e\u7269\u4f53\u306e\u4e00\u90e8\u306e\u88dc\u9593<\/a><\/td><\/td>\n<\/tr>\n
\u6625\u65e5\u73b2\u4eba<\/td>\u30ab\u30d7\u30bb\u30eb\u69cb\u9020\u3092\u52a0\u3048\u305f\u97f3\u58f0\u5f37\u8abf\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u6027\u80fd\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
2020\u5e74\u5ea6<\/td>\u52a0\u702c\u88d5\u5927<\/td>\u30a2\u30c6\u30f3\u30b7\u30e7\u30f3\u6a5f\u69cb\u306b\u3088\u308b\u30c6\u30ad\u30b9\u30c8\u97f3\u58f0\u5408\u6210\u624b\u6cd5\u306e\u767a\u8a71\u81ea\u7136\u6027\u306e\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
\u9ad9\u6a4b\u6176\u591a<\/td>\u6b21\u4e16\u4ee3\u81ea\u52d5\u8eca\u306e\u63a5\u8fd1\u901a\u5831\u97f3\u306b\u5bfe\u3059\u308b\u8a8d\u77e5\u5bb9\u6613\u6027\u306e\u8a55\u4fa1\u624b\u6cd5\u306e\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
\u9ad8\u6a4b\u6602\u5927<\/td>\u30a2\u30f3\u30b5\u30f3\u30d6\u30eb\u306e\u305f\u3081\u306e\u4f34\u594f\u30d1\u30fc\u30c8\u7de8\u66f2\u306b\u304a\u3051\u308b\u6f14\u594f\u3057\u3084\u3059\u3055\u8a55\u4fa1\u65b9\u6cd5\u306e\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
\u5229\u6839\u5ddd\u6dbc\u4ecb<\/td>\u30de\u30b9\u30af\u7d50\u5408\u3068\u5207\u308a\u629c\u304d\u753b\u50cf\u3092\u7528\u3044\u305fCNN\u753b\u50cf\u54c1\u8cea\u8a55\u4fa1\u30b7\u30b9\u30c6\u30e0\u306e\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
\u6c38\u76db\u821c\u592a<\/td>\u6642\u9593\u4f9d\u5b58\u306e\u306a\u3044\u7279\u5fb4\u91cf\u3092\u7528\u3044\u305f\u97f3\u58f0\u5f37\u8abfDNN\u30e2\u30c7\u30eb\u306e\u6027\u80fd\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
\u6751\u4e0a\u980c<\/td>\u30ae\u30bf\u30fc\u306e\u548c\u97f3\u6f14\u594f\u306b\u304a\u3051\u308b\u548c\u97f3\u540d\u63a8\u5b9a\u624b\u6cd5\u306e\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
2019\u5e74\u5ea6<\/td>\u753a\u7530 \u822a<\/td>AWGN\u30c1\u30e3\u30cd\u30eb\u306b\u304a\u3051\u308b\u96d1\u97f3\u5206\u6563\u3092\u7528\u3044\u306a\u3044\u30d6\u30e9\u30a4\u30f3\u30c9\u5909\u8abf\u691c\u51fa<\/a><\/td><\/td>\n<\/tr>\n
\u660e\u5ca1 \u5553\u54c9<\/td>TV\u6b63\u5247\u3092\u52a0\u3048\u305f\u30b9\u30d1\u30fc\u30b9\u753b\u50cf\u8868\u73fe\u306b\u3088\u308b\u96d1\u97f3\u9664\u53bb<\/a><\/td><\/td>\n<\/tr>\n
\u6b66\u85e4 \u548c\u5e0c<\/td>2\u6b21\u5143\u7573\u307f\u8fbc\u307f\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306b\u3088\u308b\u30d4\u30a2\u30ce\u591a\u91cd\u97f3\u306e\u97f3\u9ad8\u8a8d\u8b58<\/a><\/td><\/td>\n<\/tr>\n
\u5ee3\u91ce \u5149\u661f<\/td>\u30ab\u30d7\u30bb\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7528\u3044\u305f\u97f3\u58f0\u8a8d\u8b58<\/a><\/td><\/td>\n<\/tr>\n
\u7a74\u4e45\u4fdd \u4e00\u8f1d<\/td>\u5b9f\u74b0\u5883\u3092\u60f3\u5b9a\u3057\u305f\u6b21\u4e16\u4ee3\u81ea\u52d5\u8eca\u63a5\u8fd1\u901a\u77e5\u97f3\u306e\u8a8d\u77e5\u8ddd\u96e2\u8a55\u4fa1\u6cd5\u306e\u63d0\u6848<\/a><\/td><\/td>\n<\/tr>\n
2018\u5e74\u5ea6<\/td>\u6c60\u4e0a \u5f81\u4eba<\/td>\u30b5\u30d6\u30d0\u30f3\u30c9\u5206\u89e3\u3068\u91cd\u307f\u4ed8\u3051\u3092\u7528\u3044\u305fk-SVD\u306b\u3088\u308b\u753b\u50cf\u306e\u96d1\u97f3\u9664\u53bb<\/a><\/td><\/td>\n<\/tr>\n
\u938c\u7530 \u62d3\u4e5f<\/td>\u5468\u671f\u9a12\u97f3\u306e\u305f\u3081\u306e\u80fd\u52d5\u9a12\u97f3\u5236\u5fa1\u6cd5\u306b\u95a2\u3059\u308b\u4e00\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
\u583a\u4e95 \u6176\u592a<\/td>VQ-VAE\u306b\u3088\u308b\u97f3\u58f0\u5fa9\u5143\u7cbe\u5ea6\u306e\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
\u4f50\u4e45\u9593 \u5357\u6d77<\/td>\u6f5c\u5728\u5909\u6570\u6b63\u5247\u5316\u306b\u3088\u308bDNN\u3092\u7528\u3044\u305f\u97f3\u58f0\u5f37\u8abf\u6cd5\u306e\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
\u6fa4\u6751 \u52c7\u6597<\/td>\u9806\u5e8f\u7d71\u8a08\u91cf\u3092\u7528\u3044\u305f\u7573\u307f\u8fbc\u307f\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af<\/a><\/td><\/td>\n<\/tr>\n
2017\u5e74\u5ea6<\/td>\u68ee \u5eb7\u4e00<\/td>\u9069\u5fdcOFDM\u74b0\u5883\u4e0b\u3067\u306e\u4f1d\u9001\u8def\u7279\u6027\u3092\u8003\u616e\u3057\u305f\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u30d6\u30e9\u30a4\u30f3\u30c9\u5909\u8abf\u691c\u51fa<\/a><\/td><\/td>\n<\/tr>\n
\u5149\u4e95 \u52c7\u4eba<\/td>\u81ea\u52d5\u63a1\u8b5c\u306b\u304a\u3051\u308b\u97f3\u9ad8\uff0c\u767a\u97f3\u6642\u523b\u63a8\u5b9a\u306b\u304a\u3051\u308b\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
\u5bcc\u6c38 \u76f4\u6a39<\/td>\u6df1\u5c64\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7528\u3044\u305f\u97f3\u58f0\u5f37\u8abf\u306e\u6027\u80fd\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
\u91ce\u53e3 \u967d\u592a<\/td>\u6df1\u5c64\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u3092\u7528\u3044\u305f\u5ba2\u89b3\u7684\u753b\u50cf\u54c1\u8cea\u8a55\u4fa1\u30b9\u30b3\u30a2\u306e\u7d44\u307f\u5408\u308f\u305b<\/a><\/td><\/td>\n<\/tr>\n
\u5ca9\u5143 \u8cb4\u54c9<\/td>\u9aa8\u5c0e\u97f3\u58f0\u306e\u305f\u3081\u306e\u30d5\u30a9\u30eb\u30de\u30f3\u30c8\u5468\u6ce2\u6570\u63a8\u5b9a\u6cd5\u306e\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
2016\u5e74\u5ea6<\/td>\u4e00\u689d \u6167
\n<\/td>		\u9069\u5fdcOFDM\u306e\u5909\u8abf\u691c\u51fa\u306b\u304a\u3051\u308b\u96d1\u97f3\u5206\u6563\u3092\u8003\u616e\u3057\u305f\u6e96\u6700\u9069\u6700\u5c24\u63a8\u5b9a\u6cd5\u306e\u958b\u767a<\/a><\/td><\/td>\n<\/tr>\n
\u4eca\u91ce \u907c\u592a\u90ce
\n<\/td>		MIMO\u306b\u304a\u3051\u308b\u96d1\u97f3\u5206\u6563\u3092\u8003\u616e\u3057\u305fQRM-MLD\u6cd5\u306e\u6027\u80fd\u6539\u5584<\/a><\/td><\/td>\n<\/tr>\n
\u9234\u6728 \u826f\u5553
\n<\/td>		\u96d1\u97f3\u306b\u9811\u5f37\u306a\u8a71\u8005\u8a8d\u8b58\u306e\u305f\u3081\u306e\u57fa\u672c\u5468\u6ce2\u6570\u3092\u7528\u3044\u305f\u6df1\u5c64\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af<\/a><\/td><\/td>\n<\/tr>\n
\u9ad8\u5d8b \u6e09
\n<\/td>		\u697d\u5668\u8a8d\u8b58\u306b\u304a\u3051\u308b\u7573\u307f\u8fbc\u307f\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u69cb\u9020\u306b\u95a2\u3059\u308b\u57fa\u790e\u8abf\u67fb<\/a><\/td><\/td>\n<\/tr>\n
\u6e21\u908a \u5927\u8cb4<\/td>\u9aa8\u5c0e\u97f3\u58f0\u306e\u54c1\u8cea\u6539\u5584\u306e\u305f\u3081\u306e\u6df1\u5c64\u30cb\u30e5\u30fc\u30e9\u30eb\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u69cb\u9020\u306e\u691c\u8a0e<\/a><\/td><\/td>\n<\/tr>\n
2015\u5e74\u5ea6<\/td>\u6d45\u548c \u99ff
\n<\/td>		\u30b9\u30da\u30af\u30c8\u30eb\u5305\u7d61\u60c5\u5831\u3092\u5229\u7528\u3059\u308b\u72ed\u5e2f\u57df\u97f3\u58f0\u306e\u5e2f\u57df\u62e1\u5f35<\/a><\/td><\/td>\n<\/tr>\n
\u77f3\u5c71 \u5553
\n<\/td>		3\u7a2e\u985e\u306e\u8a55\u4fa1\u5024\u3092\u4f75\u7528\u3057\u305f\u5ba2\u89b3\u7684\u753b\u50cf\u54c1\u8cea\u8a55\u4fa1 <\/a><\/td><\/td>\n<\/tr>\n
\u5c0f\u5ddd \u6c38\u7b56
\n<\/td>		\u30b7\u30f3\u30dc\u30eb\u30a4\u30f3\u30bf\u30ea\u30fc\u30d6\u306b\u3088\u308bUWB\u901a\u4fe1\u306b\u304a\u3051\u308b\u72ed\u5e2f\u57df\u5e72\u6e09\u8efd\u6e1b <\/a><\/td><\/td>\n<\/tr>\n
\u4e0a\u6751 \u97ff
\n<\/td>		\u9aa8\u5c0e\u97f3\u58f0\u306e\u305f\u3081\u306e\u767a\u8a71\u5185\u5bb9\u30fb\u8a71\u8005\u306b\u4f9d\u5b58\u3057\u306a\u3044\u30d5\u30a3\u30eb\u30bf\u8a2d\u8a08 <\/a><\/td><\/td>\n<\/tr>\n
\u4e09\u8c37 \u606d\u5e73<\/td>\u76f8\u4e92\u76f8\u95a2\u95a2\u6570\u3078\u4f4d\u76f8\u3092\u4ed8\u4e0e\u3057\u305f\u97f3\u58f0\u5f37\u8abf <\/a><\/td><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\n\n\n

\u4fee\u58eb\u8ad6\u6587<\/strong><\/p>\n\n\n\n\n\n\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t\n\t
2024\u5e74\u5ea6<\/td>\u7b20\u5009\u9678<\/td>\u4f4d\u76f8\u5909\u8abf\u306b\u57fa\u3065\u304f\u96fb\u5b50\u900f\u304b\u3057\u3092\u7528\u3044\u305f\u5230\u6765\u6642\u9593\u5dee\u63a8\u5b9a\u306e\u54c1\u8cea\u5411\u4e0a<\/a><\/td>\n<\/tr>\n
\u5409\u826f\u9752\u7a7a<\/td>\u4e0d\u660e\u77ad\u97f3\u58f0\u306e\u6587\u5b57\u8a8d\u8b58\u7387\u5411\u4e0a\u3068\u660e\u77ad\u97f3\u58f0\u306e\u5408\u6210<\/a><\/td>\n<\/tr>\n
\u8239\u6a4b\u5c1a\u5c06<\/td>\u30de\u30eb\u30c1\u30bf\u30b9\u30af\u578b\u81ea\u52d5\u5909\u8abf\u5206\u985e\u306e\u8efd\u91cf\u5316\u624b\u6cd5\u306e\u691c\u8a0e<\/a><\/td>\n<\/tr>\n
\u539f\u7530\u96bc\u592a\u6717<\/td>ChatGPT\u3092\u7528\u3044\u305f\u697d\u66f2\u751f\u6210AI\u3078\u306e\u30d7\u30ed\u30f3\u30d7\u30c8\u6700\u9069\u5316<\/a><\/td>\n<\/tr>\n
\u5317\u6761\u62d3\u5df3<\/td>\u30ae\u30bf\u30fc\u6f14\u594f\u8a55\u4fa1\u30b7\u30b9\u30c6\u30e0\u306e\u305f\u3081\u306e\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u4f5c\u6210\u304a\u3088\u3073\u30e2\u30c7\u30eb\u69cb\u7bc9<\/a><\/td>\n<\/tr>\n
\u91ce\u53e3\u51cc\u6c70<\/td>\u91cd\u307f\u3065\u3051\u5468\u6ce2\u6570\u9818\u57dfFxLMS\u3092\u7528\u3044\u305f\u30d5\u30a3\u30fc\u30c9\u30d0\u30c3\u30af\u80fd\u52d5\u9a12\u97f3\u5236\u5fa1<\/a><\/td>\n<\/tr>\n
\u6c60\u7530\u5c1a\u9a0e<\/td>\u30c6\u30ad\u30b9\u30c8\u30d7\u30ed\u30f3\u30d7\u30c8\u306b\u3088\u308b\u697d\u5668\u30d1\u30fc\u30c8\u5358\u4f4d\u306e\u697d\u66f2\u7de8\u96c6AI<\/a><\/td>\n<\/tr>\n
LIN YIFENG<\/td>\u30b9\u30de\u30fc\u30c8\u30d5\u30a9\u30f3\u306e\u52a0\u901f\u5ea6\u30bb\u30f3\u30b5\u3092\u7528\u3044\u305f\u97f3\u58f0\u5f37\u8abf<\/a><\/td>\n<\/tr>\n
2023\u5e74\u5ea6<\/td>\u5b89\u5f66 \u62d3\u6d77<\/td>\u822a\u7a7a\u5199\u771f\u3092\u7528\u3044\u305f\u5199\u771f\u753b\u50cf\u306b\u5bfe\u3059\u308b\u6761\u4ef6\u4ed8\u304d\u753b\u50cf\u88dc\u5b8c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af<\/a><\/td>\n<\/tr>\n
\u6625\u65e5 \u73b2\u4eba<\/td>\u97f3\u58f0\u5f37\u8abf\u6027\u80fd\u6539\u5584\u306b\u5411\u3051\u305f\u30c7\u30fc\u30bf\u62e1\u5f35\u624b\u6cd5\u306e\u6539\u826f<\/a><\/td>\n<\/tr>\n
\u5c71\u672c \u548c\u5f25<\/td>\u8907\u6570\u30b9\u30d4\u30fc\u30ab\u306b\u304a\u3051\u308bGCC\u2011PHAT\u6cd5\u306b\u57fa\u3065\u304f\u5230\u6765\u6642\u9593\u5dee\u63a8<\/a><\/td>\n<\/tr>\n
\u5bae\u672c \u5468<\/td>\u5e2f\u57df\u5236\u5fa1\u3092\u5fdc\u7528\u3057\u305f\u885b\u661f\u901a\u4fe1\u306eACM\u52b9\u7387\u5316<\/a><\/td>\n<\/tr>\n
\u7be0\u7530 \u958b\u6597<\/td>\u30d5\u30a3\u30ae\u30e5\u30a2\u30b9\u30b1\u30fc\u30c8\u306e\u30b8\u30e3\u30f3\u30d7\u56de\u8ee2\u5224\u5b9a\u30a2\u30eb\u30b4\u30ea\u30ba\u30e0<\/a><\/td>\n<\/tr>\n
\u516b\u5e61 \u5bff\u5f25<\/td>\u7279\u5b9a\u65b9\u5411\u304b\u3089\u306e\u9ad8\u9a12\u97f3\u306b\u5bfe\u3059\u308b\u97f3\u6e90\u5206\u96e2\u3092\u7528\u3044\u305f\u80fd\u52d5\u9a12\u97f3\u5236\u5fa1<\/a><\/td>\n<\/tr>\n
\u843d\u5408 \u4eae<\/td>\u30b0\u30e9\u30d5\u4fe1\u53f7\u51e6\u7406\u3092\u7528\u3044\u305f\u30a8\u30c3\u30b8\u62bd\u51fa\u3068\u305d\u306e\u5fdc\u7528<\/a><\/td>\n<\/tr>\n
\u9577\u5cf6\u305b\u308a\u3042<\/td>\u5358\u773c\u753b\u50cf\u3092\u7528\u3044\u305f\u8996\u5dee\u753b\u50cf\u751f\u6210\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u691c\u8a0e<\/a><\/td>\n<\/tr>\n
\u4f50\u85e4 \u60a0<\/td>\u67d4\u8edf\u306a\u97f3\u58f0\u5408\u6210\u306e\u305f\u3081\u306e\u9854\u578b\u62e1\u6563\u30e2\u30c7\u30eb\u3092\u4f7f\u7528\u3057\u305f\u97f3\u58f0\u30d1\u30e9\u30e1\u30fc\u30bf\u5316<\/a><\/td>\n<\/tr>\n
2022\u5e74\u5ea6<\/td>\u65b0\u660e\u76f4\u6597<\/td>\u5236\u7d04\u4ed8\u304d\u30dc\u30eb\u30c4\u30de\u30f3\u30de\u30b7\u30f3\u3092\u7528\u3044\u305f\u6b4c\u5531\u8a55\u4fa1\u30e2\u30c7\u30eb\u306e\u69cb\u7bc9<\/a><\/td>\n<\/tr>\n
\u5229\u6839\u5ddd\u6dbc\u4ecb<\/td>\u5370\u5237\u54c1\u8cea\u8a55\u4fa1\u306e\u305f\u3081\u306e\u4e3b\u89b3\u8a55\u4fa1\u30c7\u30fc\u30bf\u30bb\u30c3\u30c8\u306e\u4f5c\u6210<\/a><\/td>\n<\/tr>\n
\u6751\u4e0a\u980c<\/td>\u500d\u97f3\u306b\u3088\u308b\u5f71\u97ff\u3092\u8003\u616e\u3057\u305f\u30ae\u30bf\u30fc\u306e\u548c\u97f3\u540d\u8a8d\u8b58\u65b9\u6cd5<\/a><\/td>\n<\/tr>\n
2021\u5e74\u5ea6<\/td>\u753a\u7530\u822a<\/td>\u30de\u30eb\u30c1\u30bf\u30b9\u30af\u5b66\u7fd2\u3092\u7528\u3044\u305fSNR\u63a8\u5b9a\u306b\u57fa\u3065\u304f\u81ea\u52d5\u5909\u8abf\u5206\u985e<\/a><\/td>\n<\/tr>\n
\u6b66\u85e4\u548c\u5e0c<\/td>\u56de\u5e30\u30e6\u30cb\u30c3\u30c8\u4ed8\u304dAttention\u3092\u7528\u3044\u305f\u30a4\u30f3\u30b9\u30bf\u30f3\u30b9\u30bb\u30b0\u30e1\u30f3\u30c6\u30fc\u30b7\u30e7\u30f3\u306b\u3088\u308b\u81ea\u52d5\u63a1\u8b5c<\/a><\/td>\n<\/tr>\n
YUWEN TAI<\/td>Two-Stage Filter Response Normalization Network for Real Image Denoising<\/a><\/td>\n<\/tr>\n
2020\u5e74\u5ea6<\/td>\u938c\u7530 \u62d3\u4e5f<\/td>\u9069\u5fdc\u30ce\u30c3\u30c1\u30d5\u30a3\u30eb\u30bf\u3092\u7528\u3044\u305f\u8907\u6570\u5468\u671f\u9a12\u97f3\u306e\u80fd\u52d5\u5236\u5fa1<\/a><\/td>\n<\/tr>\n
\u583a\u4e95 \u6176\u592a<\/td>\u67d4\u8edf\u306a\u58f0\u8cea\u5909\u63db\u306e\u305f\u3081\u306e\u58f0\u8cea\u30d1\u30e9\u30e1\u30fc\u30bf\u62bd\u51fa<\/a><\/td>\n<\/tr>\n
\u6fa4\u6751 \u52c7\u6597<\/td>\u30df\u30ea\u6ce2\u30ec\u30fc\u30c0\u3092\u7528\u3044\u305f\u30e2\u30c7\u30eb\u30d9\u30fc\u30b9\u306e\u8eca\u4e21\u4f4d\u7f6e\u30fb\u65b9\u5411\u63a8\u5b9a<\/a><\/td>\n<\/tr>\n
\u9ad9\u6749 \u9678<\/td>\u72ed\u5e2f\u57df\u9a12\u97f3\u5236\u5fa1\u306e\u305f\u3081\u306e\u7dda\u5f62\u4e88\u6e2c\u5668\u3092\u7528\u3044\u305f\u80fd\u52d5\u9a12\u97f3\u5236\u5fa1<\/a><\/td>\n<\/tr>\n
\u5149\u4e95 \u52c7\u4eba<\/td>\u30bd\u30fc\u30b9\u30d5\u30a3\u30eb\u30bf\u578b\u97f3\u58f0\u5408\u6210\u306e\u6575\u5bfe\u7684\u5b66\u7fd2\u306b\u3088\u308b\u6700\u9069\u5316<\/a><\/td>\n<\/tr>\n
\u4f50\u4e45\u9593 \u5357\u6d77<\/td>\u96d1\u97f3\u6291\u5236\u6027\u80fd\u5411\u4e0a\u306b\u5411\u3051\u305f\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u97f3\u58f0\u5f37\u8abf\u6cd5<\/a><\/td>\n<\/tr>\n
2019\u5e74\u5ea6<\/td>\u5bcc\u6c38 \u76f4\u6a39<\/td>\u97f3\u58f0\u306e\u5206\u5e03\u3092\u8003\u616e\u3057\u305f\u6df1\u5c64\u5b66\u7fd2\u306b\u3088\u308b\u97f3\u58f0\u5f37\u8abf<\/a><\/td>\n<\/tr>\n
\u68ee \u5eb7\u4e00<\/td>\u753b\u50cf\u88dc\u5b8c\u30cd\u30c3\u30c8\u30ef\u30fc\u30af\u306e\u305f\u3081\u306e\u30a8\u30c3\u30b8\u60c5\u5831\u306b\u57fa\u3065\u304f\u6575\u5bfe\u7684\u5b66\u7fd2\u6a5f<\/a><\/td>\n<\/tr>\n
2018\u5e74\u5ea6<\/td>\u4e00\u689d \u6167<\/td>\u30ce\u30f3\u30d1\u30e9\u30e1\u30c8\u30ea\u30c3\u30af\u306a\u5c24\u5ea6\u95a2\u6570\u306b\u3088\u308b\u30d6\u30e9\u30a4\u30f3\u30c9\u5909\u8abf\u691c\u51fa<\/a><\/td>\n<\/tr>\n
\u4eca\u91ce \u907c\u592a\u90ce<\/td>MIMO\u306b\u304a\u3051\u308b\u30b9\u30d1\u30fc\u30b9\u901a\u4fe1\u8def\u306e\u305f\u3081\u306e\u30d6\u30e9\u30a4\u30f3\u30c9\u63a8\u5b9a\u6cd5<\/a><\/td>\n<\/tr>\n
\u9234\u6728 \u826f\u5553<\/td>\u30df\u30ea\u6ce2\u30ec\u30fc\u30c0\u30fc\u3092\u7528\u3044\u305f\u8eca\u4e21\u4f4d\u7f6e\u63a8\u5b9a\u30b7\u30b9\u30c6\u30e0<\/a><\/td>\n<\/tr>\n
\u9ad8\u5d8b \u6e09
\n<\/td>		\u9069\u5fdc\u30d3\u30fc\u30e0\u30d5\u30a9\u30fc\u30df\u30f3\u30b0\u306b\u3088\u308b\u97f3\u58f0\u5f37\u8abf\u6cd5\u306e\u6027\u80fd\u6539\u5584<\/a><\/td>\n<\/tr>\n
\u675c \u601d\u8061
\n<\/td>		\u96d1\u97f3\u74b0\u5883\u4e0b\u3067\u306e\u9ad8\u7cbe\u5ea6\u57fa\u672c\u5468\u6ce2\u6570\u62bd\u51fa\u306e\u305f\u3081\u306e\u30bc\u30ed\u7f6e\u63db\u97f3\u58f0\u5f37\u8abf\u6cd5\u3092\u7528\u3044\u305f\u30e9\u30b0\u7a93\u6cd5\u306e\u6539\u5584<\/a><\/td>\n<\/tr>\n
2017\u5e74\u5ea6<\/td>\u6d45\u548c \u99ff<\/td>\u7121\u58f0\u5b50\u97f3\u533a\u9593\u691c\u51fa\u3068\u72ed\u5e2f\u57df\u97f3\u58f0\u306e\u5e2f\u57df\u62e1\u5f35<\/a><\/td>\n<\/tr>\n
\u77f3\u5c71 \u5553<\/td>\u5ba2\u89b3\u7684\u753b\u50cf\u54c1\u8cea\u8a55\u4fa1\u6cd5\u306e\u7c21\u7565\u5316\u3068\u6027\u80fd\u6539\u5584<\/a><\/td>\n<\/tr>\n
\u5c0f\u5ddd \u6c38\u7b56<\/td>\u7121\u7dda\u901a\u4fe1\u306b\u304a\u3051\u308b\u30b7\u30f3\u30dc\u30eb\u4e88\u6e2c\u3092\u7528\u3044\u305f\u72ed\u5e2f\u57df\u5e72\u6e09\u8efd\u6e1b<\/a><\/td>\n<\/tr>\n
\u4e0a\u6751 \u97ff<\/td>\u30de\u30a4\u30af\u30ed\u30db\u30f3\u30a2\u30ec\u30a4\u3092\u7528\u3044\u305f\u97f3\u58f0\u5f37\u8abf\u306e\u6539\u5584\u624b\u6cd5\u306b\u95a2\u3059\u308b\u7814\u7a76<\/a><\/td>\n<\/tr>\n
\u4e09\u8c37 \u606d\u5e73<\/td>\u7a93\u306a\u3057\u91cd\u307f\u4ed8\u304d\u81ea\u5df1\u76f8\u95a2\u6cd5\u3092\u7528\u3044\u305f\u57fa\u672c\u5468\u6ce2\u6570\u63a8\u5b9a\u304a\u3088\u3073Non-Local Means\u3092\u7528\u3044\u305f\u97f3\u58f0\u5f37\u8abf<\/a><\/td>\n<\/tr>\n
2016\u5e74\u5ea6<\/td>\u5c0f\u690b \u7406\u4eba<\/td>\u30aa\u30fc\u30c7\u30a3\u30aa\u96fb\u5b50\u900f\u304b\u3057\u306e\u7279\u6027\u6539\u5584\u306b\u95a2\u3059\u308b\u7814\u7a76<\/a><\/td>\n<\/tr>\n
\u571f\u65b9 \u6b63\u548c<\/td>\u30d1\u30ef\u30fc\u30b9\u30da\u30af\u30c8\u30eb\u306e\u30d2\u30b9\u30c8\u30b0\u30e9\u30e0\u3092\u7528\u3044\u305f\u30df\u30e5\u30fc\u30b8\u30ab\u30eb\u30ce\u30a4\u30ba\u306e\u6291\u5727\u624b\u6cd5\u306e\u63d0\u6848<\/a><\/td>\n<\/tr>\n
\u803f \u660e\u6708<\/td>Noise Subtraction and Pitch Synchronous Addition for LPC Analysis of Noisy Speech<\/a><\/td>\n<\/tr>\n
\u5f35 \u8a69\u9298<\/td>\u96d1\u97f3\u74b0\u5883\u4e0b\u3067\u306e\u9ad8\u7cbe\u5ea6\u306a\u57fa\u672c\u5468\u6ce2\u6570\u62bd\u51fa\u306e\u305f\u3081\u306e\u6c17\u5c0e\u97f3\u58f0\u304a\u3088\u3073\u9aa8\u5c0e\u97f3\u58f0\u306e\u540c\u6642\u5229\u7528<\/a><\/td>\n<\/tr>\n
\u5468 \u5929\u6d0b<\/td>\u96d1\u97f3\u91cd\u7573\u753b\u50cf\u304b\u3089\u306e\u5fa9\u5143\u306e\u305f\u3081\u306e\u53cd\u5fa9\u62e1\u5f35\u30b9\u30da\u30af\u30c8\u30eb\u5f15\u304d\u7b97\u6cd5<\/a><\/td>\n<\/tr>\n
2015\u5e74\u5ea6<\/td>\u5ca9\u4e95 \u512a<\/td>\u9ad8\u96d1\u97f3\u74b0\u5883\u4e0b\u306b\u304a\u3051\u308b\u96f6\u7f6e\u63db\u4fe1\u53f7\u3092\u7528\u3044\u305f\u97f3\u58f0\u5f37\u8abf <\/a><\/td>\n<\/tr>\n
\u8c4a\u5cf6 \u96c5\u5927<\/td>\u7dda\u5f62\u4e88\u6e2c\u306b\u3088\u308b\u30d1\u30b1\u30c3\u30c8\u30ed\u30b9\u96a0\u853d\u306e\u7279\u6027\u6539\u5584\u3068\u305d\u306e\u6027\u80fd\u8a55\u4fa1<\/a><\/td>\n<\/tr>\n
\u534a\u7530 \u4fca\u4ecb<\/td>\u9aa8\u5c0e\u97f3\u58f0\u3067\u306e\u30b9\u30da\u30af\u30c8\u30eb\u5305\u7d61\u306e\u91cd\u8981\u6027\u3068\u6df1\u5c64\u5b66\u7fd2\u3092\u7528\u3044\u305f\u660e\u77ad\u5ea6\u6539\u5584\u624b\u6cd5\u306e\u691c\u8a0e<\/a><\/td>\n<\/tr>\n
CHU HONGXIANG<\/td>PTS Method for PAPR Reduction Without Side Information in OFDM Systems <\/a><\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"

\u53d7\u8cde IEEE Pacific Rim Conference on Communications, Computers and Signal Processing, Gold Paper Award (Best Pape […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":200,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-2905","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/www.sie.ics.saitama-u.ac.jp\/index.php\/wp-json\/wp\/v2\/pages\/2905","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.sie.ics.saitama-u.ac.jp\/index.php\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/www.sie.ics.saitama-u.ac.jp\/index.php\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/www.sie.ics.saitama-u.ac.jp\/index.php\/wp-json\/wp\/v2\/users\/1"}],"replies":[{"embeddable":true,"href":"https:\/\/www.sie.ics.saitama-u.ac.jp\/index.php\/wp-json\/wp\/v2\/comments?post=2905"}],"version-history":[{"count":12,"href":"https:\/\/www.sie.ics.saitama-u.ac.jp\/index.php\/wp-json\/wp\/v2\/pages\/2905\/revisions"}],"predecessor-version":[{"id":3421,"href":"https:\/\/www.sie.ics.saitama-u.ac.jp\/index.php\/wp-json\/wp\/v2\/pages\/2905\/revisions\/3421"}],"wp:attachment":[{"href":"https:\/\/www.sie.ics.saitama-u.ac.jp\/index.php\/wp-json\/wp\/v2\/media?parent=2905"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}