Implementation of the backpropagation algorithm on iPSC/2 hypercube multicomputer system
Author
Ercoşkun, Deniz
Advisor
Oflazer, Kemal
Date
1990Publisher
Bilkent University
Language
English
Type
ThesisItem Usage Stats
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Abstract
Backpropagation is a supervised learning procedure for a class of artificial
neural networks. It has recently been widely used in training such neural
networks to perform relatively nontrivial tasks like text-to-speech conversion
or autonomous land vehicle control. However, the slow rate of convergence
of the basic backpropagation algorithm has limited its application to rather
small networks since the computational requirements grow significantly as the
network size grows. This thesis work presents a parallel implementation of the
backpropagation learning algorithm on a hypercube multicomputer system.
The main motivation for this implementation is the construction of a parallel
training and simulation utility for such networks, so that larger neural network
applications can be experimented with.