Threshold Noise as a Source of Volatility in Random Synchronous Asymmetric Neural Networks
Bohr, Henrik · McGuire, Patrick · Pershing, Chris · Rafelski, Johann
Disordered Systems and Neural Networks
Adaptation and Self-Organizing Systems
Biological Physics
Neurons and Cognition
Original · EN
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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