Continuous attractors of a class of neural networks with a large number of neurons |
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| Authors: | Fang Xu Zhang Yi |
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| Affiliation: | a School of Sciences, Southwest Petroleum University, Chengdu 610500, PR Chinab Machine Intelligence Laboratory, College of Computer Science, Sichuan University, Chengdu 610065, PR China |
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| Abstract: | A class of simplified background neural networks model with a large number of neurons is proposed. Continuous attractors of the simplified model are studied in this paper. It contains: (1) When the background inputs are set to zero and the excitatory connections are in Gaussian shape, continuous attractors of the new network are obtained under some condition. (2) When the background inputs are nonzero and the excitatory connections are still in Gaussian shape, continuous attractors are achieved under some appropriately selected condition. (3) Discussions and examples are used to illustrate the theories developed. |
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| Keywords: | Background neural networks Continuous attractors Taylor&rsquo s theorem |
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