Application of interpattern association to gray-level neural net

Chii-Maw Uang; Francis T. S. Yu

doi:10.1117/12.131221

30 October 1992 Application of interpattern association to gray-level neural net

Chii-Maw Uang, Francis T. S. Yu

Proceedings Volume 1812, Optical Computing and Neural Networks; (1992) https://doi.org/10.1117/12.131221
Event: International Symposium on Optoelectronics in Computers, Communications, and Control, 1992, Hsinchu, Taiwan

Abstract

A gray level discrete associative memory (GLDAM) neural network using interpattern association (IPA) model is presented. By decomposing a gray level pattern into bipolar/binary modes of subpatterns, a GLDAM can be constructed. Although GLDAM improves the information capacity of the neural net, the decomposition process introduces sparse allocation in memory matrix, which affects the performance of the neural net. Computer simulated results for the Hopfield and the IPA models are provided, in which we have shown that the IPA GLDAM performs better.

Citation Download Citation

Chii-Maw Uang and Francis T. S. Yu "Application of interpattern association to gray-level neural net", Proc. SPIE 1812, Optical Computing and Neural Networks, (30 October 1992); https://doi.org/10.1117/12.131221

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