A memristor-based circuit design of avoidance learning with time delay and its application

IF 3.1 3区 工程技术 Q2 NEUROSCIENCES
Junwei Sun, Haojie Wang, Yuanpeng Xu, Peng Liu, Yanfeng Wang
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Abstract

Currently, the research in memristor-based associative memory neural networks pays more attention to positive stimuli and lays less attention to negative stimuli. Negative stimuli are superior to positive stimuli in some ways, but lack the associated circuit implementation. In this paper, a memristor-based circuit design of avoidance learning with time delay is designed. The circuit can respond to a negative stimulus after initial avoidance learning and the effect of delay time between stimuli is considered. The realization of avoidance learning is confirmed in the PSPICE simulation results. In addition, an extended application circuit based on the memristor-based circuit design of avoidance learning with time delay is proposed. The application circuit is based on the advantage of negative stimuli is more difficult to forget than positive stimuli in associative memory. Based on the features of objects as input, the output of the circuit is used to achieve the function of avoidance learning. The application circuit provides more references for neural networks of automatic driving with further development.

Abstract Image

基于忆阻器的时延回避学习电路设计及其应用
目前,基于忆阻器的联想记忆神经网络研究更多地关注正面刺激,而较少关注负面刺激。负刺激在某些方面优于正刺激,但缺乏相关的电路实现。本文设计了一种基于忆阻器的时延回避学习电路。该电路可在初始回避学习后对负刺激做出反应,并考虑了刺激之间延迟时间的影响。PSPICE 仿真结果证实了回避学习的实现。此外,还提出了基于忆阻器电路设计的具有时间延迟的回避学习扩展应用电路。该应用电路基于联想记忆中负面刺激比正面刺激更难遗忘的优势。以对象的特征为输入,利用电路的输出实现回避学习的功能。该应用电路为自动驾驶神经网络的进一步发展提供了更多参考。
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来源期刊
Cognitive Neurodynamics
Cognitive Neurodynamics 医学-神经科学
CiteScore
6.90
自引率
18.90%
发文量
140
审稿时长
12 months
期刊介绍: Cognitive Neurodynamics provides a unique forum of communication and cooperation for scientists and engineers working in the field of cognitive neurodynamics, intelligent science and applications, bridging the gap between theory and application, without any preference for pure theoretical, experimental or computational models. The emphasis is to publish original models of cognitive neurodynamics, novel computational theories and experimental results. In particular, intelligent science inspired by cognitive neuroscience and neurodynamics is also very welcome. The scope of Cognitive Neurodynamics covers cognitive neuroscience, neural computation based on dynamics, computer science, intelligent science as well as their interdisciplinary applications in the natural and engineering sciences. Papers that are appropriate for non-specialist readers are encouraged. 1. There is no page limit for manuscripts submitted to Cognitive Neurodynamics. Research papers should clearly represent an important advance of especially broad interest to researchers and technologists in neuroscience, biophysics, BCI, neural computer and intelligent robotics. 2. Cognitive Neurodynamics also welcomes brief communications: short papers reporting results that are of genuinely broad interest but that for one reason and another do not make a sufficiently complete story to justify a full article publication. Brief Communications should consist of approximately four manuscript pages. 3. Cognitive Neurodynamics publishes review articles in which a specific field is reviewed through an exhaustive literature survey. There are no restrictions on the number of pages. Review articles are usually invited, but submitted reviews will also be considered.
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