net = mlpinit(net, prior)
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).
mlp, mlpprior, mlppak, mlpunpakCopyright (c) Ian T Nabney (1996-9)