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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 bysampling <CODE>t</CODE> at equal intervals and then generating target data bycomputing <CODE>t + 0.3*sin(2*pi*t)</CODE> and adding Gaussian noise. AMixture Density Network with 3 centres in the mixture model is trainedby minimizing a negative log likelihood error function using the scaledconjugate gradient optimizer. <p>The conditional means, mixing coefficients and variances are plottedas a function of <CODE>x</CODE>, and a contour plot of the full conditionaldensity 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>⌨️ 快捷键说明
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