diff toolboxes/FullBNT-1.0.7/netlab3.3/mlpinit.m @ 0:e9a9cd732c1e tip

first hg version after svn

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/toolboxes/FullBNT-1.0.7/netlab3.3/mlpinit.m	Tue Feb 10 15:05:51 2015 +0000
@@ -0,0 +1,31 @@
+function net = mlpinit(net, prior)
+%MLPINIT Initialise the weights in a 2-layer feedforward network.
+%
+%	Description
+%
+%	NET = MLPINIT(NET, PRIOR) takes a 2-layer feedforward network NET and
+%	sets the weights and biases by sampling from a Gaussian distribution.
+%	If PRIOR is a scalar, then all of the parameters (weights and biases)
+%	are sampled from a single isotropic Gaussian with inverse variance
+%	equal to PRIOR. If PRIOR is a data structure of the kind generated by
+%	MLPPRIOR, then the parameters are sampled from multiple Gaussians
+%	according to their groupings (defined by the INDEX field) with
+%	corresponding variances (defined by the ALPHA field).
+%
+%	See also
+%	MLP, MLPPRIOR, MLPPAK, MLPUNPAK
+%
+
+%	Copyright (c) Ian T Nabney (1996-2001)
+
+if isstruct(prior)
+  sig = 1./sqrt(prior.index*prior.alpha);
+  w = sig'.*randn(1, net.nwts); 
+elseif size(prior) == [1 1]
+  w = randn(1, net.nwts).*sqrt(1/prior);
+else
+  error('prior must be a scalar or a structure');
+end  
+
+net = mlpunpak(net, w);
+