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23rd International Conference on Neural Information Processing (ICONIP)

作者： Fujii, Takashi Ito, Hidetaka Miyoshi, Seiji Kansai Univ Grad Sch Sci & Engn 3-3-35 Yamate Cho Suita Osaka 5648680 Japan Kansai Univ Fac Engn Sci 3-3-35 Yamate Cho Suita Osaka 5648680 Japan

ISBN: (纸本)9783319466729;9783319466712

We analyze the dynamical behaviors of semi-supervised learning in the framework of on-line learning by using the statistical-mechanical method. A student uses several correlated input vectors in each update. The student is given a desired output for only one input vector out of these correlated input vectors. In this model, we derive simultaneous differential equations with deterministic forms that describe the dynamical behaviors of order parameters using the self-averaging property in the thermodynamic limit. We treat the Hebbian and Perceptron learning rules. As a result, it is shown that using unlabeled data is effective in the early stages for both of the two learning rules. In addition, we show that the two learning rules have qualitatively different dynamical behaviors. Furthermore, we propose a new algorithm that improves the generalization performance by switching the number of input vectors used in an update as the time step proceeds.

关键词： On-line learning Semi-supervised learning statistical-mechanical method Thermodynamic limit Optimal scheduling

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statistical-mechanical analysis of the FXLMS algorithm with actual primary path 40

Statistical-mechanical analysis of the FXLMS algorithm with ...

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40th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2015

作者： Miyoshi, Seiji Kajikawa, Yoshinobu Faculty of Engineering Science Kansai University 3-3-35 Yamate-cho Suita-shi Osaka Japan

ISBN: (纸本)9781467369978

A theory that predicts the behaviors of the Filtered-X LMS algorithm was derived by using a statistical-mechanical method. In this paper, the theory is generalized to explain the system behaviors in the case of an actual primary path. In the theory, cross-correlations between the element of a primary path and that of an adaptive filter and autocorrelations of the elements of the adaptive filter are treated as macroscopic variables. Simultaneous differential equations that describe the dynamical behaviors of the macroscopic variables are obtained under conditions in which the tapped-delay line is sufficiently long. The equations are analytically solved to obtain the correlations and finally compute the mean-square error. In order to generalize the theory to the case of an actual primary path, the correlations of the elements of the primary path are absorbed. The generalized theory quantitatively predict the behaviors in the case of an actual primary path. © 2015 IEEE.

关键词： active noise control actual primary path adaptive filter Filtered-X LMS algorithm statistical-mechanical method

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statistical-mechanical Analysis of Adaptive Volterra Filter for Nonwhite Input Signals

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IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES 2024年第1期E107A卷 87-95页

作者： Kugiyama, Koyo Miyoshi, Seiji Kansai Univ Fac Engn Sci Dept Elect Elect & Informat Engn Suita 5648680 Japan

The Volterra filter is one of the digital filters that can describe nonlinearity. In this paper, we analyze the dynamic behaviors of an adaptive signal processing system with the Volterra filter for nonwhite input signals by a statistical -mechanical method. Assuming the self -averaging property with an infinitely long tapped -delay line, we derive simultaneous differential equations that describe the behaviors of macroscopic variables in a deterministic and closed form. We analytically solve the derived equations to reveal the effect of the nonwhiteness of the input signal on the adaptation process. The results for the second -order Volterra filter show that the nonwhiteness decreases the mean -square error (MSE) in the early stages of the adaptation process and increases the MSE in the later stages.

关键词： Volterra filter adaptive filter statistical-mechanical method LMS algorithm

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statistical-mechanical analysis of the FXLMS algorithm with actual primary path

Statistical-mechanical analysis of the FXLMS algorithm with ...

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IEEE International Conference on Acoustics, Speech and Signal Processing

作者： S. Miyoshi Y. Kajikawa Fac. of Eng. Sci. Kansai Univ. Suita Japan

ISBN: (纸本)9781467369985

关键词： Filtered-X LMS algorithm active noise control actual primary path adaptive filter statistical-mechanical method adaptive filters Active noise control Byways Least mean square algorithm system behavior Elements

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