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Iterative Middle Mapping Learning Algorithm for Cellular Neural Networks
Chen HE Akio USHIDA
IEICE TRANSACTIONS on Fundamentals of Electronics, Communications and Computer Sciences
Publication Date: 1994/04/25
Print ISSN: 0916-8508
Type of Manuscript: PAPER
Category: Neural Networks
cellular neural networks, associative memory, learning algorithm,
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In this paper, a middle-mapping learning algorithm for cellular associative memories is presented. This algorithm makes full use of the properties of the cellular neural network so that the associative memory has some advantages compared with the memory designed by the ourter product method. It can guarantee each prototype is stored at an equilibrium point. In the practical implementation, it is easy to build up the circuit because the weight matrix presenting the connection between cells is not symmetric. The synchronous updating rule makes its associative speed very fast compared to the Hopfield associative memory.