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• W1887755351 abstract "This paper studies a cascade system of dynamic binary neural networks. The system is characterized by signum activation function, ternary connection parameters, and integer threshold parameters. As a fundamental learning problem, we consider storage and stabilization of one desired binary periodic orbit that corresponds to control signals of switching circuits. For the storage, we present a simple method based on the correlation learning. For the stabilization, we present a sparsification method based on the mutation operation in the genetic algorithm. Using the Gray-code-based return map, the storage and stability can be investigated. Performing numerical experiments, effectiveness of the learning method is confirmed." @default.
• W1887755351 created "2016-06-24" @default.
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• W1887755351 date "2015-01-01" @default.
• W1887755351 modified "2023-09-28" @default.
• W1887755351 title "A Cascade System of Dynamic Binary Neural Networks and Learning of Periodic Orbit" @default.
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• W1887755351 doi "https://doi.org/10.1587/transinf.2014opp0011" @default.
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