NISHI Tetsuo Kyushu Univ., Fac. of Eng., Professor, 工学部, 教授 (40037908)
UEDA Yoshisuke Kyoto Univ., Fac. of Eng., Professor, 工学部, 教授 (00025959)
MORI Shisaku Kyushu Univ., Fac. of Sci. and Tech., Professor, 理工学部, 教授 (00051269)
AMARI Shun'ichi Univ. of Tokyo Fac. of Eng., Professor, 工学部, 教授 (80010726)
HORIUCHI Kazuo Waseda Univ., Sch. of Sci. and Eng., Professor, 理工学部, 教授 (90063403)
|Budget Amount *help
¥5,100,000 (Direct Cost : ¥5,100,000)
Fiscal Year 1991 : ¥2,400,000 (Direct Cost : ¥2,400,000)
Fiscal Year 1990 : ¥2,700,000 (Direct Cost : ¥2,700,000)
This co-operative research has been done during the period from May, 1990 to March, 1992. The purpose of the research is to do a systematic research on neurodynamics. The followings are main results obtained in this research :
(1) Neurocomputing :
Neurocomputing is a style of information processing. An excellent and recent review on neurocomputing is surveyed. In this review, the follwing is emphasized : modern technology has been so developed that neurocomputing can be implemented in computer systems and in neurodevices.
(2) Neuron Models and Their Dynamics :
Periodic response characteristic of a simple nerve membrane model named two-factor two-mode model stimulated periodically is reported. On the other hand, a model of a chaotic neural network is summarized and its associative dynamics is discussed. Furthermore, dynamical universality of neural networks is reviewed.
(3) Mathematical Aspects of Neuro-Dynamics for Combinatorial Optimization and Optimization Algorithms :
Hopfield's neural ne
tworks are known to have a potentiality to solve combinatorial optimization problems. It is, however, found that the networks often fail to get the optimum solution. Mathematical aspects of neuro-dynamics for combinatorial optimization is discussed. Furthermore, two optimization algorithms are presented : The former is an efficient algorithm for finding all of the global minimum points of Hopfiefd's type energy functions ; the latter is the one using Logit transformation.
(4) Associative Memory in Neural Networks :
A synthesis procedure for a discrete asynchronous neural network is presented. Moreover, the number of stable equilibrium points of a class of Hopfield Networks is developed. On the other hand, an analogy between Markov chain and the asynchronous memory recall process of Hebbian-type associative memory is developed.
(5) Applications of Neural Networks to Engineering :
Image compression and regeneration by nonlinear associative silicon retina is discussed. Moreover, a cloning template for celluar neural network is reported. Furthermore, separating capabilities of three layer neural networks are surveyed.
(6) Dynamics in Nonlinear Networks :
An extension of the Lienard theorem and its application is developed. Moreover, mode locking and chaos in a forced self-oscillatory systems with spatial degrees of freedom are discussed.
Furthermore, synchronization of chaotic states in a chemical oscillator is discussed.
(7) Mathematical analysis of Nonlinear systems :
Functional Analysis of nonlinear system fluctuation is developed. Moreover, nonlinear functional analysis and self-validating numerics is reviewed.
(8) Holding of open Research Meetings
Co-sponsored by the Technical Group on Nonlinear Problem (NLP) of IEICE and the one on Circuits and Systems (CAS), an open research meeting was held on July 15-17, 1991 at Shikano-shima in Fukuoka. Also on January 31, 1992, second open research meeting was held at Waseda University co-sponsored by NLP and CAS.
The special issue of the transactions of IEICE on Nonlinear Theory and Its Applications was published on June, 1991. Also the one on Nonlinear Dynamics-Adaptive, Learning, and Neural Systems will be published on May, 1992. Both of these issues where a main part of the fruits of the research is published are edited by the members of the research. Less