Memristor-Based Circuit Implementations of Recognition Network and Recall Network With Forgetting Stages

This paper proposes a novel memistor-based neuron circuit, in which the memristor-CMOS hybrid synaptic circuit simply utilizes the positive voltage to change the memristance. At the same time, in order to obtain the memristance and output voltage changes in the neuron circuit, a mathematical deduction is implemented according to the circuit structure. Then, the memristor-based recognition and recall network circuits are constructed based on the proposed neuron circuit. The recognition and recall functions are realized by associative learning between the unconditional stimuli and the conditional stimuli (CS). After the learning stages, the single presentation of CS activates forgetting stages in the two networks. Furthermore, the related parameter changes in the learning and forgetting stages can be calculated by the deduced equations approximately. The PSPICE simulations are implemented to demonstrate the effectiveness of the proposed circuits and the deduced equations.