Trainable ISTA for sparse signal recovery D Ito, S Takabe, T Wadayama IEEE Transactions on Signal Processing 67 (12), 3113-3125, 2019 | 212 | 2019 |
A typical reconstruction limit for compressed sensing based on lp-norm minimization Y Kabashima, T Wadayama, T Tanaka Journal of Statistical Mechanics: Theory and Experiment 2009 (09), L09003, 2009 | 212 | 2009 |
Gradient descent bit flipping algorithms for decoding LDPC codes T Wadayama, K Nakamura, M Yagita, Y Funahashi, S Usami, I Takumi IEEE Transactions on Communications 58 (6), 1610-1614, 2010 | 193 | 2010 |
Low-density parity-check matrices for coding of correlated sources J Muramatsu, T Uyematsu, T Wadayama IEEE transactions on information theory 51 (10), 3645-3654, 2005 | 94 | 2005 |
Trainable projected gradient detector for massive overloaded MIMO channels: Data-driven tuning approach S Takabe, M Imanishi, T Wadayama, R Hayakawa, K Hayashi IEEE Access 7, 93326-93338, 2019 | 79 | 2019 |
A coded modulation scheme based on low density parity check codes T Wadayama IEICE transactions on fundamentals of electronics, communications and …, 2001 | 63 | 2001 |
Introduction to Low Density Parity Check Codes and Sum-Product Algorithm T Wadayama Technical Report of the Institute of Electronics, Information and …, 2001 | 56 | 2001 |
Coded M-FSK for power line communications AJH Vinck, J Haering, T Wadayama 2000 IEEE International Symposium on Information Theory (Cat. No. 00CH37060 …, 2000 | 51 | 2000 |
Interior point decoding for linear vector channels based on convex optimization T Wadayama IEEE transactions on information theory 56 (10), 4905-4921, 2010 | 48* | 2010 |
Gradient descent bit flipping algorithms for decoding LDPC codes T Wadayama, K Nakamura, M Yagita, Y Funahashi, S Usami, I Takumi 2008 International Symposium on Information Theory and Its Applications, 1-6, 2008 | 44 | 2008 |
Low density parity check matrices for coding of multiple access networks J Muramatsu, T Uyematsu, T Wadayama Proceedings 2003 IEEE Information Theory Workshop (Cat. No. 03EX674), 304-307, 2003 | 44 | 2003 |
Deep learning-aided projected gradient detector for massive overloaded MIMO channels S Takabe, M Imanishi, T Wadayama, K Hayashi ICC 2019-2019 IEEE International Conference on Communications (ICC), 1-6, 2019 | 40 | 2019 |
An analysis on non-adaptive group testing based on sparse pooling graphs T Wadayama 2013 IEEE International Symposium on Information Theory, 2681-2685, 2013 | 35* | 2013 |
An iterative decoding algorithm of low density parity check codes for hidden Markov noise channels T Wadayama ISITA2000, Hawaii, Nov., 2000 | 34 | 2000 |
LP-decodable permutation codes based on linearly constrained permutation matrices T Wadayama, M Hagiwara IEEE transactions on information theory 58 (8), 5454-5470, 2012 | 32 | 2012 |
Deep learning-aided trainable projected gradient decoding for LDPC codes T Wadayama, S Takabe 2019 IEEE International Symposium on Information Theory (ISIT), 2444-2448, 2019 | 29 | 2019 |
A multilevel construction of permutation codes T Wadayama, H AJ IEICE transactions on fundamentals of electronics, communications and …, 2001 | 28 | 2001 |
A cutting-plane method based on redundant rows for improving fractional distance M Miwa, T Wadayama, I Takumi IEEE Journal on Selected Areas in Communications 27 (6), 1005-1012, 2009 | 27 | 2009 |
Upper and Lower Bounds on Maximum Nonlinearity of n-input m-output Boolean Function T Wadayama, T Hada, K Wakasugi, M Kasahara Designs, Codes and Cryptography 23, 23-34, 2001 | 26 | 2001 |
Deep learning-based average consensus M Kishida, M Ogura, Y Yoshida, T Wadayama IEEE Access 8, 142404-142412, 2020 | 24 | 2020 |