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A Developmental Model for the Evolution of Artificial Neural Networks
J.C.Astor,C.Adami   We present a model of decentralized growth and development for artificial neural networks (ANNs), inspired by developmental biology and the physiology of nervous systems. In this model, each individual artificial neuron is an autonomous unit whose behavior is determined only by the genetic information it harbors and local concentrations of substrates. The chemicals and substrates, in turn, are modeled by a simple artificial chemistry. While the system is designed to allow for the evolution of complex networks, we demonstrate the power of the artificial chemistry by analyzing engineered (handwritten) genomes that lead to the growth of simple networks with behaviors known from physiology. To evolve more complex structures, a Java-based, platformindependent, asynchronous, distributed genetic algorithm (GA) has been implemented that allows users to participatein evolutionary experiments via the World Wide Web. 1634
BP神经网络分类器C程序
j_si94   本程序为一个误差向后传播的三层前馈神经网络有指导的学习算法。 在压缩文件中有使用说明。 j_si94的email:wjchang1994@yahoo.com.cn 2495
用神经网络进行手写字母识别
nay0648   在屏幕上书写大写字母,程序自动进行识别。程序编制运用了人工神经网络原理。 3169
铁路轨道状态检测数据处理智能分析方法
陈峰,张江 将人工神经网络的BP算法应用于轨检数据的智能处理和自动分类上。 2171
  
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