How to generate the input current for exciting a spiking neural model using the cuckoo search algorithm

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. © 2014 Springer International Publishing Switzerland.