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How to Generate the Input Current for Exciting a Spiking Neural Model Using the Cuckoo Search Algorithm

  • Roberto A. Vazquez
  • Guillermo Sandoval
  • Jose Ambrosio
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 516)

Abstract

Spiking neurons are neural models that try to simulate the behavior of biological neurons. This model generates a response (spikes or spike train) only when the model reaches a specific threshold. This response could be coded into a firing rate and perform a pattern classification task according to the firing rate generated with the input current. However, the input current must be carefully computed to obtain the desired behavior. In this paper, we describe how the Cuckoo Search algorithm can be used to train a spiking neuron and determine the best way to compute the input current for solving a pattern classification task. The accuracy of the methodology is tested using several pattern recognition problems.

Keywords

Cuckoo Search Algorithm Spiking Neural Networks Pattern recognition 

Notes

Acknowledgments

The authors would like to thank CONACYT-INEGI and Universidad La Salle for the economical support under grant number 187637 and I-061/12, respectively.

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Roberto A. Vazquez
    • 1
  • Guillermo Sandoval
    • 1
  • Jose Ambrosio
    • 1
  1. 1.Intelligent Systems GroupUniversidad La SalleMexico CityMexico

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