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date Tue, 10 Feb 2015 15:05:51 +0000
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+<html>
+<head>
+<title>
+Netlab Reference Manual demmdn1
+</title>
+</head>
+<body>
+<H1> demmdn1
+</H1>
+<h2>
+Purpose
+</h2>
+Demonstrate fitting a multi-valued function using a Mixture Density Network.
+
+<p><h2>
+Synopsis
+</h2>
+<PRE>
+demmdn1</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>t</CODE> at equal intervals and then generating target data by
+computing <CODE>t + 0.3*sin(2*pi*t)</CODE> and adding Gaussian noise. A
+Mixture Density Network with 3 centres in the mixture model is trained
+by minimizing a negative log likelihood error function using the scaled
+conjugate gradient optimizer. 
+
+<p>The conditional means, mixing coefficients and variances are plotted
+as a function of <CODE>x</CODE>, and a contour plot of the full conditional
+density is also generated.
+
+<p><h2>
+See Also
+</h2>
+<CODE><a href="mdn.htm">mdn</a></CODE>, <CODE><a href="mdnerr.htm">mdnerr</a></CODE>, <CODE><a href="mdngrad.htm">mdngrad</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>
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