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authorziejd22017-09-28 15:04:40 -0500
committerziejd22017-09-28 15:04:40 -0500
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downloadBNW-8070dc963753142bb86c4ed698d91fd623ed28e7.tar.gz
BNW using Octave instead of Matlab.
This version of BNW should perform the same as the original version. The only difference is that it uses Octave instead of Matlab when running BayesNet Toolbox during parameter learning.

I am calling this BNW_1.02. It can be accessed at:
compbio.uthsc.edu/BNW_1.02
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+<html>
+<head>
+<title>
+Netlab Reference Manual demopt1
+</title>
+</head>
+<body>
+<H1> demopt1
+</H1>
+<h2>
+Purpose
+</h2>
+Demonstrate different optimisers on Rosenbrock's function.
+
+<p><h2>
+Synopsis
+</h2>
+<PRE>
+demopt1
+demopt1(xinit)
+</PRE>
+
+
+<p><h2>
+Description
+</h2>
+The four general optimisers (quasi-Newton, conjugate gradients, 
+scaled conjugate gradients, and gradient descent) are applied to
+the minimisation of Rosenbrock's well known `banana' function.
+Each optimiser is run for at most 100 cycles, and a stopping
+criterion of 1.0e-4 is used for both position and function value.
+At the end, the trajectory of each algorithm is shown on a contour
+plot of the function.
+
+<p><CODE>demopt1(xinit)</CODE> allows the user to specify a row vector with
+two columns as the starting point.  The default is the point [-1 1].
+Note that the contour plot has an x range of [-1.5, 1.5] and a y
+range of [-0.5, 2.1], so it is best to choose a starting point in the
+same region.
+
+<p><h2>
+See Also
+</h2>
+<CODE><a href="conjgrad.htm">conjgrad</a></CODE>, <CODE><a href="graddesc.htm">graddesc</a></CODE>, <CODE><a href="quasinew.htm">quasinew</a></CODE>, <CODE><a href="scg.htm">scg</a></CODE>, <CODE><a href="rosen.htm">rosen</a></CODE>, <CODE><a href="rosegrad.htm">rosegrad</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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