Learning with single quadratic integrate-and-fire neuron

Authors:
Deepak Mishra;Abhishek Yadav;Prem K. Kalra
Affiliations:
Department of Electrical Engineering, IIT Kanpur, India;Department of Electrical Engineering, G.B. Pant University of Agri. & Technology, Pant Nagar, India;Department of Electrical Engineering, IIT Kanpur, India
Venue:
ISNN'06 Proceedings of the Third international conference on Advances in Neural Networks - Volume Part I
Year:
2006

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Abstract

In this paper, a learning algorithm for a single Quadratic Integrate-and-Fire Neuron (QIFN) is proposed and tested for various applications in which a multilayer perceptron neural network is conventionally used. It is found that a single QIFN is sufficient for the applications that require a number of neurons in different layers of a conventional neural network. Several benchmark and real-life problems of classification and function-approximation have been illustrated.