遗忘
结合属性
内容寻址存储器
一般化
计算机科学
人工神经网络
强化学习
双向联想存储器
内容寻址存储
联想学习
人工智能
心理学
神经科学
数学
认知心理学
数学分析
纯数学
作者
Juntao Han,Xin Cheng,Guangjun Xie,Junwei Sun,Gang Liu,Zhang Zhang
出处
期刊:IEEE Transactions on Nanotechnology
[Institute of Electrical and Electronics Engineers]
日期:2024-01-01
卷期号:23: 35-44
标识
DOI:10.1109/tnano.2023.3346402
摘要
Reinforcement, extinction, generalization and differentiation are all basic principles of Pavlov associative memory. Most memristive neural networks that simulate associative memory only consider reinforcement and extinction, while ignoring differentiation and generalization. In this paper, a memristive circuit of associative memory with generalization and differentiation is proposed to solve the above problem. It implements the functions of learning, forgetting, long-term memory, generalization and differentiation. Learning and forgetting correspond to reinforcement and extinction in associative memory respectively. Spontaneous recovery, in which forgotten reflexes can reappear in the absence of an unconditional stimulus, is also discussed here. Besides, a special differentiation method that takes into account the time delay is designed and demonstrated. The proposed memristive circuit of associative memory provides a reference for the theoretical research and application of artificial neural networks.
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