I. Introduction

At the beginning of the computer age, there were problems that men couldn't solve, or more precisely (and this distinction is extrememly important) men were too slow in solving those problems.
So, we made a machine we called computer which would be able to automate some solutions of problems that were causing trouble to humans. Those problems were calculating equations to resolve important physical problems, and later displaying a nice GUI (heum that's not exactly the fact with win9x :-) ), making word processing and so on ...
But now we come to a limit with these computers and standard programming, we can't easily, and quickly perform for example :

That's why, man tried to make an intellectual abstraction wich would work mostly like human brain works, that's what we called a neuronal network.

So, the present tutorial will try to explain the principal of the neuronal network, and will show the relationship with a biological neuronal network.
After that, when the bases will be well understood, you will be shown a famous NN (neuronal network) topology called BPN (Backward propagation network). And after all, we will explain you how to use a very well implemented and simple library (as easy as possible) written in C++ that simulate The BPN and so succeded in solving very compicated problems such as pattern recognition in a very noisy environment.

Now, lets stop talking and beginning with the real tutorial :-)
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