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Comparison of LIF and Izhikevich Spiking Neural Models for Recognition of Uppercase and Lowercase English Characters

Soni Chaturvedi, Neha R. Sondhiya, Rutika N. Titre, Dr.A.A. Khurshid, Dr. S.S. Dorle

Abstract


This paper depicts pattern classification of uppercase and lower case English character, using Leaky integrated and fire neuron model and Izhikevich neuron model of spiking neural network. Spiking neural network is one of the best artificial neural networks, which are widely used in the field of neuron science. In this paper we focused on spiking mechanism of both models and compare them in terms of accuracy and simulation time.

Leaky integrate and fire neuron model which is one of the simple and efficient model of spiking neural network that analyze and simulate efficiently. On the other hand Izhikevich model is one of the powerful models which can simulate thousands of neurons in real time. Using these two models simulation results are obtained for recognition of uppercase and lower case English characters. Finally we report on simulation results of both models and discuss their performance, in terms of recognition rate and speed. 


Keywords


Graphical User Interface (GUI), Izhikevich Neuron Model, Leaky Integrated and Fire Neuron Model (LIF), Spiking Neural Network (SNN).

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References


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