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| author | ziejd2 | 2018-03-14 23:23:33 -0500 |
|---|---|---|
| committer | GitHub | 2018-03-14 23:23:33 -0500 |
| commit | 1ff6baa44e22b91eefb48aea6f3befa078c0489b (patch) | |
| tree | e0fd79d2e32fd2aedda2eadaed0f19af3514c520 /sourcecodes/bnt-master/nethelp3.3/rbfgrad.htm | |
| parent | 6882395afdadf4e982b25b5215071a0932730950 (diff) | |
| parent | c80226899f5cdd9f11c163817d59445213f5bef0 (diff) | |
| download | BNW-1ff6baa44e22b91eefb48aea6f3befa078c0489b.tar.gz | |
Merge pull request #1 from ziejd2/octave_php_separate
Octave php separate
Diffstat (limited to 'sourcecodes/bnt-master/nethelp3.3/rbfgrad.htm')
| -rw-r--r-- | sourcecodes/bnt-master/nethelp3.3/rbfgrad.htm | 55 |
1 files changed, 55 insertions, 0 deletions
diff --git a/sourcecodes/bnt-master/nethelp3.3/rbfgrad.htm b/sourcecodes/bnt-master/nethelp3.3/rbfgrad.htm new file mode 100644 index 00000000..30759dfe --- /dev/null +++ b/sourcecodes/bnt-master/nethelp3.3/rbfgrad.htm @@ -0,0 +1,55 @@ +<html> +<head> +<title> +Netlab Reference Manual rbfgrad +</title> +</head> +<body> +<H1> rbfgrad +</H1> +<h2> +Purpose +</h2> +Evaluate gradient of error function for RBF network. + +<p><h2> +Synopsis +</h2> +<PRE> + +g = rbfgrad(net, x, t) +[g, gdata, gprior] = rbfgrad(net, x, t) +</PRE> + + +<p><h2> +Description +</h2> +<CODE>g = rbfgrad(net, x, t)</CODE> takes a network data structure <CODE>net</CODE> +together with a matrix <CODE>x</CODE> of input +vectors and a matrix <CODE>t</CODE> of target vectors, and evaluates the gradient +<CODE>g</CODE> of the error function with respect to the network weights (i.e. +including the hidden unit parameters). The error +function is sum of squares. +Each row of <CODE>x</CODE> corresponds to one +input vector and each row of <CODE>t</CODE> contains the corresponding target vector. +If the output function is <CODE>'neuroscale'</CODE> then the gradient is only +computed for the output layer weights and biases. + +<p><CODE>[g, gdata, gprior] = rbfgrad(net, x, t)</CODE> also returns separately +the data and prior contributions to the gradient. In the case of +multiple groups in the prior, <CODE>gprior</CODE> is a matrix with a row +for each group and a column for each weight parameter. + +<p><h2> +See Also +</h2> +<CODE><a href="rbf.htm">rbf</a></CODE>, <CODE><a href="rbffwd.htm">rbffwd</a></CODE>, <CODE><a href="rbferr.htm">rbferr</a></CODE>, <CODE><a href="rbfpak.htm">rbfpak</a></CODE>, <CODE><a href="rbfunpak.htm">rbfunpak</a></CODE>, <CODE><a href="rbfbkp.htm">rbfbkp</a></CODE><hr> +<b>Pages:</b> +<a href="index.htm">Index</a> +<hr> +<p>Copyright (c) Ian T Nabney (1996-9) + + +</body> +</html> \ No newline at end of file |