Using evolutionary algorithms for fitting high-dimensional models to neuronal data
n 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 algori...
| Main Authors: | , , |
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| Format: | Article |
| Published: |
Springer Verlag
2012
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| Online Access: | https://eprints.nottingham.ac.uk/2735/ |