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<title>Example 3 - FEED FORWARD NEURAL NETWORKS - A JAVA IMPLEMENTATION
v2.0</title>
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<b><font size="4"><a name="top"></a>FEED FORWARD NEURAL
NETWORK<span lang="tr">S</span> - A JAVA IMPLEMENTATION v2.0 </font></b>
<br><font size="5"><b>Example </b></font><span lang="tr">
<font size="5"><b>3</b></font></span></td>
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This is an example of an untypical usage of the
<span lang="tr">package</span>. We don't use pattern<span lang="tr">
</span>sets and error calculation methods, we use
incremental training with patterns created on the fly.<br>
<br>
Here we create a very simple multilayer perceptron and train
it for a simple function.<br>
<br>
- Create a multilayer perceptron with three layers: one
input layer with two units; one hidden layer with three
neurons, using tanh function; one output layer with one
neuron using linear function.<br>
- Create random input values, calculate target by the
formula y = sin ( x1 + x2 ) and train the net with these
values without using a pattern set.<br>
- Test it.</td>
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