Memristor-Based Neural Network Circuit of Full-Function Pavlov Associative Memory With Time Delay and Variable Learning Rate

• Published in: IEEE transactions on cybernetics Vol. 50; no. 7; pp. 2935 - 2945
• Main Authors: Sun, Junwei, Han, Gaoyong, Zeng, Zhigang, Wang, Yanfeng
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2020; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Associative memory; Biological neural networks; Circuit design; Circuit simulation; Computer simulation; Conditioning, Classical; Delay effects; Dogs; Electrical Equipment and Supplies; Food; Integrated circuit modeling; Learning; Machine Learning; Memory; memristor; Memristors; Models, Neurological; Modules; Neural networks; Neural Networks, Computer; Neurons; Pavlov associative memory; time delay; Time Factors; Time lag
• ISSN: 2168-2267; 2168-2275; 2168-2275
• DOI: 10.1109/TCYB.2019.2951520

Most memristor-based Pavlov associative memory neural networks strictly require that only simultaneous food and ring appear to generate associative memory. In this article, the time delay is considered, in order to form associative memory when the food stimulus lags behind the ring stimulus for a certain period of time. In addition, the rate of learning can be changed with the length of time between the ring stimulus and food stimulus. A memristive neural network circuit that can realize Pavlov associative memory with time delay is designed and verified by the simulation results. The designed circuit consists of a synapse module, a voltage control module, and a time-delay module. The functions, such as learning, forgetting, fast learning, slow forgetting, and time-delay learning, are implemented by the circuit. The Pavlov associative memory neural network with time-delay learning provides a reference for further development of the brain-like systems.