A Method for the Associative Storage of Analog Vectors

Part of Advances in Neural Information Processing Systems 2 (NIPS 1989)

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Amir Atiya, Yaser Abu-Mostafa


A method for storing analog vectors in Hopfield's continuous feed(cid:173) back model is proposed. By analog vectors we mean vectors whose components are real-valued. The vectors to be stored are set as equilibria of the network. The network model consists of one layer of visible neurons and one layer of hidden neurons. We propose a learning algorithm, which results in adjusting the positions of the equilibria, as well as guaranteeing their stability. Simulation results confirm the effectiveness of the method .