Review of Handwritten Pattern Recognition of Digits and Special Characters Using Feed Forward Neural Network and Izhikevich Neural Model

Abstract

Neural Networks are found as an effective tool for pattern recognition. In this paper a Feed Forward Neural Network and an Izhikevich neuron model is applied for pattern recognition of Digits and Special characters. Given a set of input patterns of digits and Special characters each input pattern is transformed into an input signal. Then the Feed Forward Neural Network and Izhikevich neuron model is stimulated and firing rates are computed. After adjusting the synaptic weights and the threshold values of the neural model, input patterns will generate almost the same firing rate and will recognize the patterns. At last, a comparison between a feed-forward neural network which is Artificial Neural Network model and the Izhikevich neural model which is Spiking Neural Network model is implemented in MATLAB for the handwritten Pattern recognition.