尖峰神经网络中的噪声形成-网络设计问题

C. Mayr, R. Schuffny
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引用次数: 3

摘要

近年来,人们越来越关注脉冲神经网络中的信息传递机制。特别是这些网络的噪声整形特性及其与δ - σ调制器的相似性引起了人们的广泛关注。然而,这一领域的研究很少关注这些网络中的权重对噪声整形特性的影响。本文讨论了网络运行的各种模式,以及系统生成网络权值可能产生的有利影响和不利影响。本研究与神经网络作为过采样A/D转换器构建模块的工业应用相关。此外,还列出了进一步的争论点,必须对这些争论点进行深入研究,以增加上述脉冲神经网络的适用性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Noise shaping in spiking neural nets - network design issues
In recent years, there has been an increased focus on the mechanics of information transmission in spiking neural networks. Especially the noise shaping properties of these networks and their similarity to delta-sigma modulators has received a lot of attention. However, very little of the research done in this area has focused on the effect the weights in these networks have on the noise shaping properties. This paper concerns itself with the various modes of network operation and beneficial as well as detrimental effects which the systematic generation of network weights can effect. Relevancy of this research to industrial application of neural nets as building blocks of oversampled A/D converters is shown. Also, further points of contention are listed, which must be thoroughly researched to add to the above mentioned applicability of spiking neural nets.
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