g = glmgrad(net, x, t) [g, gdata, gprior] = glmgrad(net, x, t)
g = glmgrad(net, x, t) takes a generalized linear model
data structure net
together with a matrix x of input vectors and a matrix t
of target vectors, and evaluates the gradient g of the error
function with respect to the network weights. The error function
corresponds to the choice of output unit activation function. Each row
of x corresponds to one input vector and each row of t
corresponds to one target vector.
[g, gdata, gprior] = glmgrad(net, x, t) also returns separately
the data and prior contributions to the gradient.
glm, glmpak, glmunpak, glmfwd, glmerr, glmtrainCopyright (c) Ian T Nabney (1996-9)