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Complex-valued associative memories with projection and iterative learning rules

Isokawa T., Yamamoto H., Nishimura H., Yumoto T., Kamiura N., Matsui N.

Journal of Artificial Intelligence and Soft Computing Research

2018

Vol. 8, No. 3

237--249

In this paper, we investigate the stability of patterns embedded as the associative memory distributed on the complex-valued Hopfield neural network, in which the neuron states are encoded by the phase values on a unit circle of complex plane. As learning schemes for embedding patterns onto the network, projection rule and iterative learning rule are formally expanded to the complex-valued case. The retrieval of patterns embedded by iterative learning rule is demonstrated and the stability for embedded patterns is quantitatively investigated.