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1 <html>
2 <head>
3 <title>
4 Netlab Reference Manual demprior
5 </title>
6 </head>
7 <body>
8 <H1> demprior
9 </H1>
10 <h2>
11 Purpose
12 </h2>
13 Demonstrate sampling from a multi-parameter Gaussian prior.
14
15 <p><h2>
16 Synopsis
17 </h2>
18 <PRE>
19 demprior</PRE>
20
21
22 <p><h2>
23 Description
24 </h2>
25 This function plots the functions represented by a multi-layer perceptron
26 network when the weights are set to values drawn from a Gaussian prior
27 distribution. The parameters <CODE>aw1</CODE>, <CODE>ab1</CODE> <CODE>aw2</CODE> and <CODE>ab2</CODE>
28 control the inverse variances of the first-layer weights, the hidden unit
29 biases, the second-layer weights and the output unit biases respectively.
30 Their values can be adjusted on a logarithmic scale using the sliders, or
31 by typing values into the text boxes and pressing the return key.
32
33 <p><h2>
34 See Also
35 </h2>
36 <CODE><a href="mlp.htm">mlp</a></CODE><hr>
37 <b>Pages:</b>
38 <a href="index.htm">Index</a>
39 <hr>
40 <p>Copyright (c) Ian T Nabney (1996-9)
41
42
43 </body>
44 </html>