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Generally, people tend to learn or recall pleasant experiences during positive feelings. Similarly, people tend to learn or recall unpleasant things during negative feelings. The research in psychological field has demonstrated that human memory is closely related to emotion. On one hand, emotion helps store the memory that possesses the same emotion valence, which is known as the mood congruency memory (MCM). On the other hand, memory stored in a certain emotional state will be associated easily when the same emotion occurs, which is called mood-dependent memory (MDM). Inspired by the mechanisms of MCM and MDM, a memristor-based circuit of emotion-affected associative memory neural network is proposed in this work. The designed circuit mainly contains MCM module and MDM module. The functions, such as learning, forgetting, variable learning rate, MCM effect, MDM effect, and time interval, are implemented by the circuit. The simulation results in PSPICE show that the proposed memristive circuit can learn and associate the memory based on emotional effects like humans. [ABSTRACT FROM AUTHOR]

The analog circuit design of the memristive neural network (MNN), which can automatically perform the online learning algorithm, is an open question. In this article, a memristive self-learning neuron circuit for implementing the online least mean square (LMS) algorithm is designed. Extending on the designed neuron circuit, the circuit implementation of the monolayer and multilayer neural network is proposed. The proposed neural network can automatically converge the output to the set target according to the input. The application-level validations of the circuits are done using pattern recognition and license plate detection. The performances of the designed MNN circuits and the effect of memristive variation are analyzed through PSPICE simulations. The learning accuracy of the proposed circuit for license plate detection can reach 93%. Circuit simulation results reveal that the proposed MNN circuits can accelerate the training speed and have the tolerance to the variations of the memristor. [ABSTRACT FROM AUTHOR]