文章基本信息

标题：Impulsive Neural Networks Algorithm Based on the Artificial Genome Model
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作者：Gao, Yuan ; Zheng, Na ; Hao, Nan 等
期刊名称：Journal of Networks
印刷版ISSN：1796-2056
出版年度：2014
卷号：9
期号：5
页码：1260-1267
DOI：10.4304/jnw.9.5.1260-1267
语种：English
出版社：Academy Publisher
摘要：To describe gene regulatory networks, this article takes the framework of the artificial genome model and proposes impulsive neural networks algorithm based on the artificial genome model. Firstly, the gene expression and the cell division tree are applied to generate spiking neurons with specific attributes, neural network structure, connection weights and specific learning rules of each neuron. Next, the gene segment duplications and divergence model are applied to design the evolutionary algorithm of impulsive neural networks at the level of the artificial genome. The dynamic changes of developmental gene regulatory networks are controlled during the whole evolutionary process. Finally, the behavior of collecting food for autonomous intelligent agent is simulated, which is driven by nerves. Experimental results demonstrate that the algorithm in this article has the evolutionary ability on large-scale impulsive neural networks
关键词：Artificial Gene;Cell Division Tree;Neural Connections;Learning Rules