Pulse stream current mode CMOS CNN chip

A. Paasio, A. Dawidziuk, V. Porra
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引用次数: 4

Abstract

A new idea of analog cellular neural network (CNN) VLSI implementation is described. The main problem in neural networks realization is the size of adjustable connections between neurons in the net. The weight circuits may occupy more than 90% of the single neuron space. The main advantage of current mode pulse stream neurons is small size of the weight circuit. The simplicity of the building blocks used allows one to operate them with relatively high speed. As compared with the other pulse stream circuits, this approach is based on current pulses. Therefore, for both basic neural operations, summation and multiplication are easy to implement, if only the phase is irrelevant.
脉冲流电流模式CMOS CNN芯片
提出了一种模拟细胞神经网络(CNN) VLSI实现的新思路。神经网络实现的主要问题是网络中神经元之间的可调节连接的大小。权重电路可以占据单个神经元空间的90%以上。电流模式脉冲流神经元的主要优点是权重电路体积小。所使用的构建模块的简单性允许人们以相对较高的速度操作它们。与其他脉冲流电路相比,这种方法是基于电流脉冲的。因此,对于基本的神经运算,只要相位不相关,求和和乘法都很容易实现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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