Most of the classical conditioning laws implemented by existing circuits are involved in learning and forgetting between only three neurons, and the problems between multiple neurons are not considered. In this article, a multimode generalization and differentiation circuit for the Pavlov associative memory is proposed based on memristors. The designed circuit is mainly composed of voltage control modules, synaptic neuron modules, and inhibition modules. The secondary differentiation is accomplished through the process of associative learning and forgetting among multiple neurons. The process of multiple generalization and differentiation is realized based on the nonvolatility and thresholding properties of memristors. The extinction inhibition and differentiation inhibition in forgetting is considered through the inhibition modules. The Pavlov associative memory neural network with multimodal generalization and differentiation may provide a reference for the further development of brain-like intelligence.

中文翻译：

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基于忆阻器的巴甫洛夫联想记忆多模泛化和微分神经网络电路


现有电路实现的经典条件反射定律大多只涉及三个神经元之间的学习和遗忘，而没有考虑多个神经元之间的问题。本文提出了一种基于忆阻器的巴甫洛夫联想存储器的多模式泛化和微分电路。设计的电路主要由电压控制模块、突触神经元模块和抑制模块组成。二次分化是通过多个神经元之间的联想学习和遗忘过程来完成的。基于忆阻器的非易失性和阈值特性实现了多重泛化和微分的过程。通过抑制模块来考虑遗忘中的消退抑制和分化抑制。具有多模态泛化和分化能力的巴甫洛夫联想记忆神经网络可能为类脑智能的进一步发展提供参考。