DocumentCode
295748
Title
Computational neural networks
Author
Yang, Jar-Ferr ; Chen, Chi-Ming
Author_Institution
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
Volume
3
fYear
1995
fDate
Nov/Dec 1995
Firstpage
1249
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 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
Keywords
convergence of numerical methods; functional analysis; iterative methods; mathematics computing; neural nets; search problems; computation-by-search scheme; computational neural network; convergence; hardlimiter neuron; inverse functions; rational functions; search function neuron; updated neuron; Analog circuits; Analog computers; Analytical models; Computational modeling; Computer networks; Integrated circuit interconnections; Neural networks; Neurons; Pattern classification; Quadratic programming;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1995. Proceedings., IEEE International Conference on
Conference_Location
Perth, WA
Print_ISBN
0-7803-2768-3
Type
conf
DOI
10.1109/ICNN.1995.487334
Filename
487334
Link To Document