Abstract
AbstractThe stability issues of both continuous and discrete time memristive neural networks have been investigated vastly and numerous publications have been published. This paper intends to provide compendious review on several mathematical techniques available for stability analysis of memristive neural networks including uncertain memristive neural networks, Hopefield memristive neural networks, bidirectional associative memory memristive neural networks, inertial memristive-based neural networks, and other related systems. Since the time delay as an influence on dynamic behavior of the networks, the effect of the same on different classes memristive neural networks is reviewed in detailed. Essential and adequate conditions for the stability for memristive neural networks are discussed. Finally, the future research challenges and directions on stability analysis of memristor-based neural networks are briefed.KeywordsMemristive neural networksStability analysisNeuromorphic computing (Memcomputing)
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