神经场整体性和增殖性研究与分析

信息几何是20世纪90年代初开始形成的理论，它将流形上的现代微分几何方法引入到神经计算科学中，为神经网络和信息论提供了十分有用的新的数学工具，也为大脑信息传输方式引入新的观念．以信息几何为工具，研究由全体神经网络组成的非线性空间神经场的整体不变性，分析和证明了神经场复杂结构的可分解性，提出了知识可增殖人工神经网络模型．其结果将有助于理解和解释人的感知系统的组织结构、定位机理和嵌入问题，提高神经网络复杂模型的研究水平和层次，挖掘认知科学在计算机模式上新的突破点；有助于增强神经网络的可理解性，为其提供了重要的理论基础．

Research and Analysis of Neural Field Global Architecture and Increase Ability

As a new theory that came into being in 1990's, information geometry introduces differential geometry method in computer neural science, provides a useful tool for the research of neural networks and information theory, and presents new breakthrough in the research of brain information transformation mechanism Based on information geometry, the global invariant properities of non linear space consisting of neural network models are studied The disintegration ability of the complex neural field architecture is analyzed and proved Finally, a knowledge increasable neural network model is presented The research helps to discover and understand the structure, transformation and locating mechanism of human's recognition system, stimulate the further neutral network (NN) research, and promote the research level of the connectionist model It also provides important theoretical basis for the understanding of neural network ensembles