more docu
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@@ -98,7 +98,7 @@
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second, and so on, until @c H<sub>l+1</sub> contains the weights
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from layer @c l to the output @c O.
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The output vector is then calculatd as:
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The output vector is then calculated as:
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O = I × H<sub>1</sub> × H<sub>2</sub> × H<sub>…</sub> × H<sub>l+1</sub>
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@code
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@@ -106,10 +106,10 @@
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const size_type o(2);
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NeuroNet<double, i, o> net;
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Matrix<1, i> input(1.0, 2.0, 0.0, -1.0);
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Matrix<1, o> output = net.propagate(input);
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Matrix<1, o> output = net(input);
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@endcode
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@section beuro-backward Back Propagation
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@section neuro-backward Back Propagation
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*/
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