By weight and bias layer initialization function
initwb(net,i)
initwb is a layer initialization function that initializes a layer’s
weights and biases according to their own initialization functions.
initwb(net,i) takes two arguments,
net | Neural network |
i | Index of a layer |
and returns the network with layer i’s weights and biases
updated.
You can create a standard network that uses initwb by calling
perceptron or linearlayer.
To prepare a custom network to be initialized with initwb,
Set net.initFcn to 'initlay'.
This sets net.initParam to the empty matrix [], because
initlay has no initialization parameters.
Set net.layers{i}.initFcn to
'initwb'.
Set each net.inputWeights{i,j}.initFcn to a weight
initialization function. Set each net.layerWeights{i,j}.initFcn to a weight
initialization function. Set each net.biases{i}.initFcn to a bias
initialization function. Examples of initialization functions are rands
(for weights and biases) and midpoint (for weights only).
To initialize the network, call init.
Each weight (bias) in layer i is set to new values calculated according
to its weight (bias) initialization function.
init | initlay | initnw | linearlayer | perceptron