文章基本信息

标题：A novel memristive cellular neural network with time-variant templates
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作者：Xiaofang Hu ; Xiaofang Hu ; Guanrong Chen 等
期刊名称：Perspectives in Science
印刷版ISSN：2213-0209
电子版ISSN：2213-0209
出版年度：2016
卷号：7
页码：126-132
DOI：10.1016/j.pisc.2015.11.021
语种：English
出版社：Elsevier
摘要：Summary A cellular neural network (CNN) is a massively parallel analog array processor capable of solving various complex processing problems by using specific templates that characterize the synaptic connections. The hardware implementation and applications of CNN have attracted a great deal of attention. Recently, memristors with nanometer-scale and variable gradual conductance have been exploited to make compact and programmable electric synapses. This paper proposes and studies a novel memristive CNN (Mt-CNN) with time-variant templates realized by memristor crossbar synaptic circuits. The template parameters are estimated analytically. The Mt-CNN provides a promising solution to hardware realization of real-time template updating processes, which can be used to effectively deal with various complicated problems of cascaded processing. Its effectiveness and advantages are demonstrated by practical examples of edge detection on noisy images.
关键词：Cellular neural network (CNN); Memristor; Time-variant template; Edge detection; Noise reduction;