S. Miyoshi

发表

Convergence properties of symmetric learning algorithm for pattern classification

K. Nakayama, K. Ikeda, S. Miyoshi, 1999 .

Convergence properties of symmetric learning algorithm for pattern classification

K. Nakayama, K. Ikeda, S. Miyoshi, 1998, 1998 IEEE International Joint Conference on Neural Networks Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98CH36227).

On simultaneous perturbation particle swarm optimization

Yutaka Maeda, Naoto Matsushita, Seiji Miyoshi, 2006, 2009 IEEE Congress on Evolutionary Computation.

Image Restoration and Segmentation using Region-Based Latent Variables: Bayesian Inference Based on Variational Method

Masato Okada, Seiji Miyoshi, M. Okada, 2011 .

Analysis of ensemble learning using simple perceptrons based on online learning theory

M. Okada, S. Miyoshi, K. Hara, 2004 .

Theory of Time Domain Ensemble On-Line Learning of Perceptron under the Existence of External Noise

M. Okada, S. Miyoshi, T. Uezu, 2007 .

Replica Analysis of Multiuser Detection for Code Division Multiple Access with M-Ary Phase-Shift Keying

M. Okada, S. Miyoshi, Hiroyuki Kato, 2013 .

Statistical Mechanics of Linear and Nonlinear Time-Domain Ensemble Learning

M. Okada, S. Miyoshi, 2006, cond-mat/0609568.

Statistical Mechanics of Time-Domain Ensemble Learning

M. Okada, S. Miyoshi, T. Uezu, 2006, cond-mat/0605176.

Statistical Mechanics of Online Learning for Ensemble Teachers

M. Okada, S. Miyoshi, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Analysis of On-Line Learning when a Moving Teacher Goes around a True Teacher

M. Okada, S. Miyoshi, 2005, physics/0509050.

Analysis of ensemble learning using simple perceptrons based on online learning theory

M. Okada, S. Miyoshi, K. Hara, 2004, 2004 IEEE International Joint Conference on Neural Networks (IEEE Cat. No.04CH37541).

Statistical-Mechanical Analysis of Adaptive Filter With Clipping Saturation-Type Nonlinearity

S. Miyoshi, 2021, IEEE Transactions on Signal Processing.

Statistical-Mechanical Analysis of Adaptive Volterra Filter for Time-Varying Unknown System

Y. Kajikawa, S. Miyoshi, Koyo Kugiyama, 2021, 2021 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).

FPGA Realization of Simultaneous Perturbation PSO

Yutaka Maeda, Takahiro Yamada, Seiji Miyoshi, 2011 .

21pWB-1 Quasi-supervised learning and ensemble learning

Masato Okada, Seiji Miyoshi, Kazuyuki Hara, 2007 .

Image Segmentation and Restoration Using Switching State-Space Model and Variational Bayesian Method

Masato Okada, Ken Takiyama, Seiji Miyoshi, 2012 .

Image Segmentation Using Region-Based Latent Variables and Belief Propagation

Masato Okada, Seiji Miyoshi, Ryota Hasegawa, 2011 .

A theory of the FXLMS algorithm based on statistical-mechanical method

Yoshinobu Kajikawa, Seiji Miyoshi, Y. Kajikawa, 2013, 2013 8th International Symposium on Image and Signal Processing and Analysis (ISPA).

Statistical-mechanical analysis of the FXLMS algorithm with nonwhite reference signals

Yoshinobu Kajikawa, Seiji Miyoshi, Y. Kajikawa, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Storage capacity diverges with synaptic efficiency in an associative memory model with synaptic delay and pruning

Masato Okada, Seiji Miyoshi, M. Okada, 2003, IEEE Transactions on Neural Networks.

Statistical-Mechanical Analysis of Adaptive Volterra Filter with the LMS Algorithm

Yoshinobu Kajikawa, Kimiko Motonaka, Seiji Miyoshi, 2021, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Statistical-Mechanics Approach to Theoretical Analysis of the FXLMS Algorithm

Yoshinobu Kajikawa, Seiji Miyoshi, Y. Kajikawa, 2018, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Statistical-Mechanical Analysis of Multi-channel Active Noise Control

Seiji Miyoshi, Tomoki Murata, Yoshinobu Kajikawa, 2018 .

Theoretical analysis of LMS algorithm for time-varying unknown system

Yoshinobu Kajikawa, Seiji Miyoshi, Norihiro Ishibushi, 2016, 2016 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA).

Statistical Mechanical Analysis of Active Noise Control with Time-varying Primary Path

Yoshinobu Kajikawa, Seiji Miyoshi, Nobuhiro Egawa, 2015 .

Probabilistic memory capacity of recurrent neural networks

K. Nakayama, S. Miyoshi, K. Nakayama, 1996, Proceedings of International Conference on Neural Networks (ICNN'96).

Ensemble-Teacher Learning through a Perceptron Rule with a Margin

Seiji Miyoshi, Kazuyuki Hara, S. Miyoshi, 2011, ICANN.

Obstacle avoidance using buffered voronoi cells based on local information from a laser range scanner

S. Miyoshi, K. Motonaka, 2022, Adv. Robotics.

Associative memory by recurrent neural networks with delay elements

Masato Okada, Seiji Miyoshi, Hiro-Fumi Yanai, 2002, Proceedings of the 9th International Conference on Neural Information Processing, 2002. ICONIP '02..

Non-monotonic convergence of online learning algorithms for perceptrons with noisy teacher

Kazushi Ikeda, Seiji Miyoshi, Hiroaki Hanzawa, 2018, Neural Networks.

A Theoretical Analysis of Semi-supervised Learning

Hidetaka Ito, Takashi Fujii, Seiji Miyoshi, 2016, ICONIP.

Statistical Mechanics of On-line Ensemble Teacher Learning through a Novel Perceptron Learning Rule

Seiji Miyoshi, Kazuyuki Hara, S. Miyoshi, 2016, 1608.06562.

Statistical-Mechanical Analysis of Semi-Supervised Learning and Its Optimal Scheduling

Hidetaka Ito, Takashi Fujii, Seiji Miyoshi, 2016 .

Analysis of the FXLMS algorithm with norm-constant time-varying primary path

Yoshinobu Kajikawa, Seiji Miyoshi, Norihiro Ishibushi, 2015, 2015 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA).

Statistical-mechanical analysis of the FXLMS algorithm with time-varying primary path

Yoshinobu Kajikawa, Seiji Miyoshi, Nobuhiro Egawa, 2014, Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2014 Asia-Pacific.

Online Learning through Moving Ensemble Teachers — An Exact Solution of a Linear Model —

Seiji Miyoshi, Takahiro Nabetani, S. Miyoshi, 2014 .

Convergence Properties of Perceptron Learning with Noisy Teacher

Kazushi Ikeda, Seiji Miyoshi, Hiroaki Hanzawa, 2012, IScIDE.

Theoretical discussion of the filtered-X LMS algorithm based on statistical mechanical analysis

Yoshinobu Kajikawa, Seiji Miyoshi, Y. Kajikawa, 2012, 2012 IEEE Statistical Signal Processing Workshop (SSP).

Statistical Mechanics of On-Line Learning Using Correlated Examples

Seiji Miyoshi, Kento Nakao, Yuta Narukawa, 2011, IEICE Trans. Inf. Syst..

Statistical Mechanics of On-Line Mutual Learning with Many Linear Perceptrons

Masato Okada, Seiji Miyoshi, Kazuyuki Hara, 2009 .

Statistical Mechanical Analysis of Simultaneous Perturbation Learning

Yutaka Maeda, Seiji Miyoshi, Hiroomi Hikawa, 2009, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Effect of Slow Switching of Ensemble Teachers in On-line Learning

M. Okada, S. Miyoshi, 2009 .

A Theoretical Analysis of On-Line Learning Using Correlated Examples

Seiji Miyoshi, Masafumi Matsuno, Shingo Sakurai, 2008, IEICE Trans. Fundam. Electron. Commun. Comput. Sci..

Statistical Mechanics of Nonlinear On-line Learning for Ensemble Teachers pdf

Masato Okada, Seiji Miyoshi, Hideto Utsumi, 2007, ArXiv.

Statistical Mechanics of On-line Learning when a Moving Teacher Goes around an Unlearnable True Teacher pdf

Masato Okada, Seiji Miyoshi, Masahiro Urakami, 2006, ArXiv.

Statistical-mechanical analysis of the FXLMS algorithm for multiple-channel active noise control

Yoshinobu Kajikawa, Seiji Miyoshi, Tomoki Murata, 2017, 2017 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC).

Control of a quadrotor group based on maximum hands-off distributed control

M. Nagahara, S. Miyoshi, Yuhwan Kwon, 2021, Int. J. Mechatronics Autom..

Self-Consistent Signal-to-Noise Analysis of CDMA Multiuser Detection with M-Ary Phase-Shift Keying

M. Okada, S. Miyoshi, Hiroyuki Kato, 2013 .

Effect of Slow Switching in On-line Learning for Ensemble Teachers

M. Okada, S. Miyoshi, 2008, 0805.0425.

Learning Scheme for Complex Neural Networks Using Simultaneous Perturbation

Yutaka Maeda, Seiji Miyoshi, Takahiro Yamada, 2011, ICANN.

Connecting PM and MAP in Bayesian spectral deconvolution by extending exchange Monte Carlo method and using multiple data sets

Kimiko Motonaka, Seiji Miyoshi, S. Miyoshi, 2019, Neural Networks.