Abstract
Associative memory is the process by which an association between two stimuli or a behavior and a stimulus is learned. This paper contributes to propose a memristive neural network and realize the Pavlov associative memory through (a) putting forward a novel average-input-feedback (AIF) learning law; (b) proposing a detailed two-terminal charge-controlled SPICE memristor models; (c) building a memristive neural network (MNN) circuit, for the first time, to realize the Pavlov associative memory. The results prove the effectiveness of AIF on facilitating the memristor for associative learning in memristive neural networks.
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