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Hindawi Publishing Corporation Fixed Point Theory and Applications Volume 2011, Article ID 615274, 17 pages doi:10.1155/2011/615274 Research Article Hamming Star-Convexity Packing in Information Storage Mau-Hsiang Shih and Feng-Sheng Tsai Department of Mathematics, National Taiwan Normal University, 88 Section 4, Ting Chou Road, Taipei 11677, Taiwan Correspondence should be addressed to Feng-Sheng Tsai, fstsai@abel.math.ntnu.edu.tw Received 8 December 2010; Accepted 16 December 2010 Academic Editor: Jen Chih Yao Copyright q 2011 M.-H. Shih and F.-S. Tsai. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly. | Hindawi Publishing Corporation Fixed Point Theory and Applications Volume 2011 Article ID 615274 17 pages doi 10.1155 2011 615274 Research Article Hamming Star-Convexity Packing in Information Storage Mau-Hsiang Shih and Feng-Sheng Tsai Department of Mathematics National Taiwan Normal University 88 Section 4 Ting Chou Road Taipei 11677 Taiwan Correspondence should be addressed to Feng-Sheng Tsai fstsai@abel.math.ntnu.edu.tw Received 8 December 2010 Accepted 16 December 2010 Academic Editor Jen Chih Yao Copyright 2011 M.-H. Shih and F.-S. Tsai. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited. A major puzzle in neural networks is understanding the information encoding principles that implement the functions of the brain systems. Population coding in neurons and plastic changes in synapses are two important subjects in attempts to explore such principles. This forms the basis of modern theory of neuroscience concerning self-organization and associative memory. Here we wish to suggest an information storage scheme based on the dynamics of evolutionary neural networks essentially reflecting the meta-complication of the dynamical changes of neurons as well as plastic changes of synapses. The information storage scheme may lead to the development of a complete description of all the equilibrium states fixed points of Hopfield networks a spacefilling network that weaves the intricate structure of Hamming star-convexity and a plasticity regime that encodes information based on algorithmic Hebbian synaptic plasticity. 1. Introduction The study of memory includes two important components the storage component of memory and the systems component of memory 1 2 . The first is concerned with exploring the molecular mechanisms whereby memory is stored whereas the second is concerned with analyzing the organizing .
