Improvement of bidirectional associative memories by using correlation significance

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Improvement of bidirectional associative memories by using correlation significance

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© The Institution of Electrical Engineers
Published

A correlation significance technique is introduced, which uses the significances between the training associations and between the neurons of the different fields, such that the storage capacity of Kosko bidirectional associative memories (BAMs) is improved. Based on the gradient descent method, an error function is constructed such that the maximal number of stored associations which are successfully recalled can be obtained. Finally computer simulations demonstrate that the proposed method has much better storage capacity than the existing methods.

Inspec keywords: correlation methods; neural nets; content-addressable storage; learning (artificial intelligence)

Other keywords: gradient descent method; correlation significance; bidirectional associative memories; storage capacity; computer simulations; training associations; neurons; error function

Subjects: Neural nets (theory); Storage system design; Associative storage

References

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      • B. Kosko . Bidirectional associative memories. IEEE Trans. , 49 - 60
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