Free E-Books for All !

E-Books Collection

Powerpoint Templates Collection

http://rapidshare.com/files/81357265/Powerpoint_Templates.rar.001
http://rapidshare.com/files/81357471/Powerpoint_Templates.rar.002

126 Oracle Books - Greatest Collection

http://rapidshare.com/files/81368320/126_Oracle_Books_Greatest_Collection_.rar.001
http://rapidshare.com/files/81379442/126_Oracle_Books_Greatest_Collection_.rar.002
http://rapidshare.com/files/81393885/126_Oracle_Books_Greatest_Collection_.rar.003
http://rapidshare.com/files/81411720/126_Oracle_Books_Greatest_Collection_.rar.004
http://rapidshare.com/files/81431387/126_Oracle_Books_Greatest_Collection_.rar.005
http://rapidshare.com/files/81455106/126_Oracle_Books_Greatest_Collection_.rar.006
http://rapidshare.com/files/81481121/126_Oracle_Books_Greatest_Collection_.rar.007
http://rapidshare.com/files/81512674/126_Oracle_Books_Greatest_Collection_.rar.008
http://rapidshare.com/files/81537203/126_Oracle_Books_Greatest_Collection_.rar.009

English Learning E-Books Collection

http://rapidshare.com/files/80423128/20_english-learning_ebooks.rar

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