arXiv · cond-mat/9712132
Threshold Noise as a Source of Volatility in Random Synchronous Asymmetric Neural Networks
Abstract
We study the diversity of complex spatio-temporal patterns of random synchronous asymmetric neural networks (RSANNs). Specifically, we investigate the impact of noisy thresholds on network performance and find that there is a narrow and interesting region of noise parameters where RSANNs display specific features of behavior desired for rapidly `thinking' systems: accessibility to a large set of distinct, complex patterns.
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Henrik Bohr, Patrick McGuire, Chris Pershing, Johann Rafelski. 1997-12-12. Threshold Noise as a Source of Volatility in Random Synchronous Asymmetric Neural Networks. https://arxiv.org/abs/cond-mat/9712132
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