The usage of the FPGA (Field Programmable Gate Array)
for neural network implementation provides flexibility in
programmable systems. FPGAs have higher speed and smaller
size for real time application than the VLSI design. The
reconfigurable FPGAs yield the availability of fast special
purpose hardware for wide applications. It sets the conditions
to explore new neural network algorithms and problems of a
scale that would not be feasible with conventional processor.
The goalofthis work is to realize the hardware implementation
ofneural network using FPGAs.