(Dhirubhai Ambani Institute of Information and Communication Technology, 2012) Ambasana, Nikita B.; Zaveri, Mazad S
The purpose of this thesis is to give an insight into the implementation of a system of neural
networks, for the tasks of Noise/Environment Modeling, Feature Extraction and Classification
of Noise/Environment, on a Field Programmable Gate Array (FPGA). A methodology for
creating baseline architecture for a new system of neural networks has been followed, to give
worst case estimates. After necessary analysis an estimate of hardware utilization, within a
specific FPGA (XC3S250E Spartan 3E Device) and the Time for Computation, for each of the
machines used, is given. It also summarizes the Performance-Price Ratio in terms of Time of
Computation and Hardware for Logic simplementation, for different degrees of parallelism in
the system.
