VLSI implementation of CSFN neural network for pattern recognition application

Authors:
Hamed Farshbaf;Hadi Esmaelzadeh
Affiliations:
Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran;Electrical and Computer Engineering Department, University of Tehran, Tehran, Iran
Venue:
NN'05 Proceedings of the 6th WSEAS international conference on Neural networks
Year:
2005

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Abstract

A digital implementation is presented for a neural network, which uses conic section function neurons. This network is employed in a digit pattern recognition application. The neural network is trained without any consideration about nonidealities of hardware implementation and then obtained weight parameters are converted to fixed-point bit-string format in order to hardware implementation. Number of bits used in this conversion, forces a trade off between accurate operation of the network and size of the hardware. Finding the optimum number of bits, steps are taken for implementation of network. Simulation results in different levels of design flow are presented.