Noise injection into inputs in sparsely connected Hopfield and winner-take-all neural networks

In this paper, we show that noise injection into inputs in unsupervised learning neural networks does not improve their performance as it does in supervised learning neural networks. Specifically, we show that training noise degrades the classification ability of a sparsely connected version of the...

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Bibliographic Details
Main Author: Wang, Lipo.
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2012
Subjects:
Online Access:https://hdl.handle.net/10356/94091
http://hdl.handle.net/10220/8195
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Institution: Nanyang Technological University
Language: English