ARTIFICIAL NEURAL NETWORKS TECHNOLOGY
Title : ARTIFICIAL NEURAL NETWORKS TECHNOLOGY
Pub Date : August 20 1992
Author : Dave Anderson and George McNeil
Publisher: Rome Laboratory
ISBN :
Overview :
This report is intended to help the reader understand what Artificial
Neural Networks are, how to use them, and where they are currently being
used.
Artificial Neural Networks are being touted as the wave of the future
in computing. They are indeed self learning mechanisms which don’t
require the traditional skills of a programmer. But unfortunately,
misconceptions have arisen. Writers have hyped that these neuron-inspired
processors can do almost anything. These exaggerations have created
disappointments for some potential users who have tried, and failed, to solve
their problems with neural networks. These application builders have often
come to the conclusion that neural nets are complicated and confusing.
Unfortunately, that confusion has come from the industry itself. An
avalanche of articles have appeared touting a large assortment of different
neural networks, all with unique claims and specific examples. Currently,
only a few of these neuron-based structures, paradigms actually, are being
used commercially. One particular structure, the feedforward, back-
propagation network, is by far and away the most popular. Most of the other
neural network structures represent models for “thinking” that are still being
evolved in the laboratories. Yet, all of these networks are simply tools and as
such the only real demand they make is that they require the network
architect to learn how to use them.
Download Link:
http://rapidshare.com/files/71385276/artificialneuralnetworkstech.PDF
“They [artificial neural networks] are indeed self learning mechanisms which don’t require the traditional skills of a programmer.”
Indeed. Appropriate application of artificial neural networks require the traditional skills of a statistician.
“Currently, only a few of these neuron-based structures, paradigms actually, are being used commercially.”
I suppose this depends on what one means by “few”. Artificial neural networks have been used to solve many real-world problems and reside in a number of commercially-available products. I don’t disagree with your comments about the hyperbole which sometimes surrounds neural networks, but they are good at solving certain types of problems and industry has recognized this, as evidenced by products like Falcon (fraud detection software).
the overview is the overview of the book.. not the website author’s comments.. thanks for your comments anyway…
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