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Rank-Revealing Orthogonal Decomposition in Extreme Learning Machine Design Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Evolutionary Tuning of a Pulse Mormyrid Electromotor Model to Generate Stereotyped Sequences of Electrical Pulse Intervals

Authors : Angel Lareo, Pablo Varona, F. B. Rodriguez

Published in: Artificial Neural Networks and Machine Learning – ICANN 2018

Publisher: Springer International Publishing

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Abstract

Adjusting parameters of a neural network model to reproduce complete sets of biologically plausible behaviors is a complex task, even in a well-described neural system. We show here a method for evolving a model of the mormyrid electromotor command chain to reproduce highly realistic temporal firing patterns as described by neuroethological studies in this system. Our method uses genetic algorithms for tuning unknown parameters in the synapses of the network. The developed fitting function simulates each evolved model under different network inputs and compare its output with the target patterns from the living animal. The obtained synaptic configuration can reveal new information about the functioning of electromotor systems.

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previous chapter Imbalanced Data Classification Based on MBCDK-means Undersampling and GA-ANN
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Footnotes
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Metadata
Title
Evolutionary Tuning of a Pulse Mormyrid Electromotor Model to Generate Stereotyped Sequences of Electrical Pulse Intervals
Authors
Angel Lareo
Pablo Varona
F. B. Rodriguez
Copyright Year
2018
Book
Artificial Neural Networks and Machine Learning – ICANN 2018

Print ISBN: 978-3-030-01420-9

Electronic ISBN: 978-3-030-01421-6

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-030-01421-6_35

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