Analysis of Limit-Cycles on Neural Networks with Asymmetrical Cyclic Connections Using Approximately Activation Functions

Shinya Suenaga, Yoshihiro Hayakawa, Koji Nakajima

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

We analyze the limit-cycles generated on the neural network with asymmetrical cyclic connections in continuous-time model. We analytically obtain the relations between the period of these limit-cycles and various parameters in the network using two kinds of approximately activation function, linear and high-gain limit. From consideration of these results, nonlinear characteristics appears to produce the region of attraction to the solution that has a main single-frequency component in various solution space that consists of the superposed solutions of the linear approximation,

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsMircea Gh. Negoita, Robert J. Howlett, Lakhmi C. Jain
PublisherSpringer Verlag
Pages974-980
Number of pages7
ISBN (Print)9783540301325
DOIs
Publication statusPublished - 2004 Jan 1

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3213
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Analysis of Limit-Cycles on Neural Networks with Asymmetrical Cyclic Connections Using Approximately Activation Functions'. Together they form a unique fingerprint.

Cite this