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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diff --git a/sourcecodes/bnt-master/docs/supportedModels.html b/sourcecodes/bnt-master/docs/supportedModels.html
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+ <h2><a name="models">Supported probabilistic models</h2> 
+<p> 
+It is trivial to implement all of
+the following probabilistic models using the toolbox.
+<ul> 
+<li>Static
+<ul> 
+<li> Linear regression, logistic regression, hierarchical mixtures of experts
+ 
+<li> Naive Bayes classifiers, mixtures of Gaussians,
+sigmoid belief nets
+ 
+<li> Factor analysis, probabilistic
+PCA, probabilistic ICA, mixtures of these models
+ 
+</ul> 
+ 
+<li>Dynamic
+<ul> 
+ 
+<li> HMMs, Factorial HMMs, coupled HMMs, input-output HMMs, DBNs
+ 
+<li> Kalman filters, ARMAX models, switching Kalman filters,
+tree-structured Kalman filters, multiscale AR models
+ 
+</ul> 
+ 
+<li> Many other combinations, for which there are (as yet) no names!
+ 
+</ul> 
+ 
+ 
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