Parametrical Neural Network
نویسندگان
چکیده
The storage capacity of the Hopfield model is about 15% of the network size. It can be increased significantly in the Potts-glass model of the associative memory only. In this model neurons can be in more than two different states. We show that even greater storage capacity can be achieved in the parametrical neural network (PNN) that is based on the parametrical four-wave mixing process that is well-known in nonlinear optics. We present a uniform formalism allowing us to describe both PNN and the Potts-glass associative memory. To estimate the storage capacity we use the Chebyshev-Chernov statistical technique.
منابع مشابه
Parametrical neural network based on the four-wave mixing process
We develop a formalism allowing us to describe operating of a network based on the parametrical four-wave mixing process that is well-known in nonlinear optics. It is shown that the storage capacity of such a network is higher compared with the Potts-glass neural networks. r 2003 Elsevier Science B.V. All rights reserved.
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