30 October 1992 Application of interpattern association to gray-level neural net
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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.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Chii-Maw Uang, Chii-Maw Uang, Francis T. S. Yu, Francis T. S. Yu, "Application of interpattern association to gray-level neural net", Proc. SPIE 1812, Optical Computing and Neural Networks, (30 October 1992); doi: 10.1117/12.131221; https://doi.org/10.1117/12.131221
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