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<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>⌨️ 快捷键说明
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