re each value corresponds to a pattern.

<p><CODE>[y, sigsq] = gpfwd(net, x, cninv)</CODE> uses the pre-computed inverse covariance
matrix <CODE>cninv</CODE> in the forward propagation.  This increases efficiency if
several calls to <CODE>gpfwd</CODE> are made.  

<p><h2>
Example
</h2>
The following code creates a Gaussian Process, trains it, and then plots the
predictions on a test set with one standard deviation error bars:
<PRE>

net = gp(1, 'sqexp');
net = gpinit(net, x, t);
net = netopt(net, options, x