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Journal of Computer Science and Technology

, Volume 4, Issue 3, pp 204–217 | Cite as

On pattern separating function in a two-layered random nerve net with feedforward inhibitory connections

  • Toyoshi Torioka
  • Wang Jiaye 
Regular Papers

Abstract

In this paper, we derive a theory for investigating the pattern separating function in the nerve net. Then, we consider some effects of the stochastic parameters constructing the nerve net, firing rates of the second layer and input patterns on the pattern separating function through the theory. As a result, we reveal that a nerve net excellent in pattern separating function is obtained when the stochastic parameters are selected properly. We also show that the pattern separating function is enhanced by controlling the firing rate of the second layer to a small value. Furthermore, the input patterns are separated largely when the firing rates of them are large.

Keywords

Granule Cell Firing Rate Output Function Cerebellar Cortex Input Pattern 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Science Press, Beijing China and Allerton Press Inc. 1989

Authors and Affiliations

  • Toyoshi Torioka
    • 1
  • Wang Jiaye 
    • 2
  1. 1.Technical CollegeYamaguchi UniversityJapan
  2. 2.Shandong UniversityJinan

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