期刊
NEUROCOMPUTING
卷 36, 期 -, 页码 225-233出版社
ELSEVIER SCIENCE BV
DOI: 10.1016/S0925-2312(00)00328-3
关键词
dynamic neural fields; gradient-based optimization; evolutionary optimization; population representation; primary visual cortex of cat
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.
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