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Optimization of dynamic neural fields
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DOI：10.1016/S0925-2312(00)00328-3.png)
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There is a growing interest in using dynamic neural fields for modeling biological and technical systems, but constructive ways to set up such models are still missing. We discuss gradient-based, evolutionary and hybrid algorithms for data-driven adaptation of neural field parameters. The proposed methods are evaluated using artificial and neuro-physiological data. (C) 2001 Elsevier Science B.V. All rights reserved.
Keyword:
dynamic neural fields
gradient-based optimization
evolutionary optimization
population representation
primary visual cortex of cat
期刊
IF:
6.5
论文数:
2.5W
被引数:
6.5W
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