Chaotic Associative Memory using Distributed Patterns for Image Retrieval -- Distance between Patterns and Recall Ability

Y. Osana (Japan)


Chaotic Neural Network, Image Retrieval


In this paper, we introduce a Chaotic Associative Mem ory using Distributed Patterns for image retrieval. This model is based on the Chaotic Associative Memory which can separate superimposed patterns and the Multi Winners Self-Organizing Neural Network which has the ability to generate distributed representation patterns corresponding to input in a self-organizing manner. In this model, there are correlation between the distributed representation pat terns and input patterns. The CAMDP make use of this property in order to realize the similar image retrieval.

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