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| author | ziejd2 | 2018-03-14 23:23:33 -0500 |
|---|---|---|
| committer | GitHub | 2018-03-14 23:23:33 -0500 |
| commit | 1ff6baa44e22b91eefb48aea6f3befa078c0489b (patch) | |
| tree | e0fd79d2e32fd2aedda2eadaed0f19af3514c520 /sourcecodes/bnt-master/nethelp3.3/demmlp1.htm | |
| parent | 6882395afdadf4e982b25b5215071a0932730950 (diff) | |
| parent | c80226899f5cdd9f11c163817d59445213f5bef0 (diff) | |
| download | BNW-1ff6baa44e22b91eefb48aea6f3befa078c0489b.tar.gz | |
Merge pull request #1 from ziejd2/octave_php_separate
Octave php separate
Diffstat (limited to 'sourcecodes/bnt-master/nethelp3.3/demmlp1.htm')
| -rw-r--r-- | sourcecodes/bnt-master/nethelp3.3/demmlp1.htm | 42 |
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diff --git a/sourcecodes/bnt-master/nethelp3.3/demmlp1.htm b/sourcecodes/bnt-master/nethelp3.3/demmlp1.htm new file mode 100644 index 00000000..3d9c2079 --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/demmlp1.htm @@ -0,0 +1,42 @@ +<html> +<head> +<title> +Netlab Reference Manual demmlp1 +</title> +</head> +<body> +<H1> demmlp1 +</H1> +<h2> +Purpose +</h2> +Demonstrate simple regression using a multi-layer perceptron + +<p><h2> +Synopsis +</h2> +<PRE> +demmlp1</PRE> + + +<p><h2> +Description +</h2> +The problem consists of one input variable <CODE>x</CODE> and one target variable +<CODE>t</CODE> with data generated by sampling <CODE>x</CODE> at equal intervals and then +generating target data by computing <CODE>sin(2*pi*x)</CODE> and adding Gaussian +noise. A 2-layer network with linear outputs is trained by minimizing a +sum-of-squares error function using the scaled conjugate gradient optimizer. + +<p><h2> +See Also +</h2> +<CODE><a href="mlp.htm">mlp</a></CODE>, <CODE><a href="mlperr.htm">mlperr</a></CODE>, <CODE><a href="mlpgrad.htm">mlpgrad</a></CODE>, <CODE><a href="scg.htm">scg</a></CODE><hr> +<b>Pages:</b> +<a href="index.htm">Index</a> +<hr> +<p>Copyright (c) Ian T Nabney (1996-9) + + +</body> +</html> \ No newline at end of file |
