Computational neural networks

Jar Ferr Yang, Chi Ming Chen

Research output: Contribution to conferencePaper

Abstract

In this paper, we discuss an approach for designing the computational neural network, which is mainly composed of a hardlimiter neuron, a updated neuron, and a search function neuron, to solve some computational problems. The computation-by-search (CBS) scheme can effectively solve some complicated problems in the condition that their search functions can be easily obtainable by some existing neural networks. The convergence of the suggested neural networks to achieve the solution are discussed and analyzed. Both theoretical analyses and simulated results show that the proposed neural network can effectively solve the complicated computational problems such that they belong to the rational functions or their inverse functions can be easily implemented by using an existing network.

Original languageEnglish
Pages1249-1253
Number of pages5
Publication statusPublished - 1995 Dec 1
EventProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust
Duration: 1995 Nov 271995 Dec 1

Other

OtherProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)
CityPerth, Aust
Period95-11-2795-12-01

All Science Journal Classification (ASJC) codes

  • Software

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