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1 <html>
2 <head>
3 <title>
4 Netlab Reference Manual gpgrad
5 </title>
6 </head>
7 <body>
8 <H1> gpgrad
9 </H1>
10 <h2>
11 Purpose
12 </h2>
13 Evaluate error gradient for Gaussian Process.
14
15 <p><h2>
16 Synopsis
17 </h2>
18 <PRE>
19 g = gpgrad(net, x, t)
20 </PRE>
21
22
23 <p><h2>
24 Description
25 </h2>
26 <CODE>g = gpgrad(net, x, t)</CODE> takes a Gaussian Process data structure <CODE>net</CODE> together
27 with a matrix <CODE>x</CODE> of input vectors and a matrix <CODE>t</CODE> of target
28 vectors, and evaluates the error gradient <CODE>g</CODE>. Each row
29 of <CODE>x</CODE> corresponds to one input vector and each row of <CODE>t</CODE>
30 corresponds to one target vector.
31
32 <p><h2>
33 See Also
34 </h2>
35 <CODE><a href="gp.htm">gp</a></CODE>, <CODE><a href="gpcovar.htm">gpcovar</a></CODE>, <CODE><a href="gpfwd.htm">gpfwd</a></CODE>, <CODE><a href="gperr.htm">gperr</a></CODE><hr>
36 <b>Pages:</b>
37 <a href="index.htm">Index</a>
38 <hr>
39 <p>Copyright (c) Ian T Nabney (1996-9)
40
41
42 </body>
43 </html>