Zero weight and bias initialization function


W = initzero(S,PR)
b = initzero(S,[1 1])


W = initzero(S,PR) takes two arguments,


Number of rows (neurons)


R-by-2 matrix of input value ranges = [Pmin Pmax]

and returns an S-by-R weight matrix of zeros.

b = initzero(S,[1 1]) returns an S-by-1 bias vector of zeros.


Here initial weights and biases are calculated for a layer with two inputs ranging over [0 1] and [-2 2] and four neurons.

W = initzero(5,[0 1; -2 2])
b = initzero(5,[1 1])

Network Use

You can create a standard network that uses initzero to initialize its weights by calling newp or newlin.

To prepare the weights and the bias of layer i of a custom network to be initialized with midpoint,

  1. Set net.initFcn to 'initlay'. (net.initParam automatically becomes initlay's default parameters.)

  2. Set net.layers{i}.initFcn to 'initwb'.

  3. Set each net.inputWeights{i,j}.initFcn to 'initzero'.

  4. Set each net.layerWeights{i,j}.initFcn to 'initzero'.

  5. Set each net.biases{i}.initFcn to 'initzero'.

To initialize the network, call init.

See help newp and help newlin for initialization examples.

See Also

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