This paper is concerned with the approximation of the Hindmarsh and Rose neuron model, which is able to reproduce the main neuronal behaviours, in view of its circuit implementation. The method is based on two main tools: a piecewise-linear approximation technique and bifurcation analysis. The piecewise-linear approximation of the Hindmarsh and Rose model is obtained by solving a mixed-integer optimization problem by a genetic algorithm. The result obtained exhibits a good degree of similarity to the original model, both from a qualitative and a quantitative standpoint.
On a piecewise linear approximation of the Hindmarsh-Rose neuron model via genetic algorithms suitable for hardware implementation
STORACE, MARCO
2008-01-01
Abstract
This paper is concerned with the approximation of the Hindmarsh and Rose neuron model, which is able to reproduce the main neuronal behaviours, in view of its circuit implementation. The method is based on two main tools: a piecewise-linear approximation technique and bifurcation analysis. The piecewise-linear approximation of the Hindmarsh and Rose model is obtained by solving a mixed-integer optimization problem by a genetic algorithm. The result obtained exhibits a good degree of similarity to the original model, both from a qualitative and a quantitative standpoint.
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