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Using Evolutionary Algorithms for Fitting High-Dimensional Models to Neuronal Data
In the study of neurosciences, and of complex biological systems in general, there is frequently a need to fit mathematical models with large numbers of parameters to highly complex datasets. Here we consider algorithms of two different classes, gradient following (GF) methods and evolutionary algor...
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| 主要な著者: | , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Springer-Verlag
2012
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC3272374/ https://ncbi.nlm.nih.gov/pubmed/22258828 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s12021-012-9140-7 |
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