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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