A Full-Functional Pavlov Associative Memory Biomimetic Neural Circuit with Memcapacitor

Most associative memory neural networks have traditionally been implemented using memristors. However, memcapacitors, which are capable of simulating the biological behavior of neurons, exhibit characteristics that are often more advantageous than memristors in realizing pavlov associative memory neural networks. This article proposes a neural network architecture based on memcapacitors. Within this framework, we have successfully implemented five classical conditional reflex functions, including learning and forgetting, time interval conditioning, time delay conditioning and blocking. The design involves the interconnection of five similar neuron modules through various synapses. This memcapacitive biomimetic neural circuit not only offers a comprehensive platform for the realization of five classical conditional reflexes but also exhibits scalability.