一种新的电流模式可编程细胞神经网络

L. Ravezzi, G. Dalla Betta, G. Setti
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引用次数: 3

摘要

本文报道了一种1.2 /spl mu/m CMOS技术的全模拟电流模式CNN的设计,其芯具有固有的重量控制能力、低功耗和占地面积小的特点。电路仿真验证了设计方法,并预测了CNN的电气性能;实验结果表明,该方法可以成功地应用于图像处理领域。初步的CNN测试芯片由8/spl倍/1阵列组成,用于连接元件检测和阴影检测,目前正在IRST (Trento Italy)以2.5 /spl mu/m的CMOS技术制造。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A new current mode programmable cellular neural network
We report on the design of a full-analog current-mode CNN in a 1.2 /spl mu/m CMOS technology, whose cell core is characterized by an intrinsic capability of weights control, low power consumption and small area occupation. Circuit simulations allowed the design approach to be validated and the electrical performance of the CNN to be predicted; moreover, it is shown that the proposed CNN can be successfully adopted for several applications in image processing. A preliminary CNN test-chip consisting of a 8/spl times/1 array for connected component detection and shadow detection, is currently being fabricated at IRST (Trento Italy) in a 2.5 /spl mu/m CMOS technology.
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