Paper:
Fast Prototyping of Artificial Neural Network: GSN Digital Implementation
SIMÕES, E.V., UEBEL, L.F., BARONE, D.A.C.
IV International Conference on Microelectronics for Neural Network and Fuzzy Systems, Torino, Italy, Sep., 1994. pp. 192-201.
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Abstract:
This work describes a framework for a GSN (Goal Seeking Neuron) Boolean neural network
fast prototyping into a FPGA (Field-Programmable Gate Array). This system provides a VHDL language
description of the trained network, allowing the direct implementation of the circuit on an
academic FPGA. A GSN software tool was designed to train and
simulate a user-defined network, with diverse dimensions and applications. The implemented
network presents 60 neurons in four pyramids with four layers. The short propagation time
(30 ns) of the network output provides the requirements to deal with real time neural
applications
Eduardo do Valle Simões,
simoes@icmc.usp.br
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