Neural Network Toolbox™

Nguyen-Widrow layer initialization function

Syntax

• net = initnw(net,i)
  

Description

initnw is a layer initialization function that initializes a layer's weights and biases according to the Nguyen-Widrow initialization algorithm. This algorithm chooses values in order to distribute the active region of each neuron in the layer approximately evenly across the layer's input space. The values contain a degree of randomness, so they are not the same each time this function is called.

initnw(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.

Network Use

You can create a standard network that uses initnw by calling newff or newcf.

To prepare a custom network to be initialized with initnw,

1. Set net.initFcn to 'initlay'. This sets net.initParam to the empty matrix [], because initlay has no initialization parameters.
2. Set net.layers{i}.initFcn to 'initnw'.

To initialize the network, call init. See newff and newcf for training examples.

Algorithm

The Nguyen-Widrow method generates initial weight and bias values for a layer so that the active regions of the layer's neurons are distributed approximately evenly over the input space.

Advantages over purely random weights and biases are

• Few neurons are wasted (because all the neurons are in the input space).
• Training works faster (because each area of the input space has neurons). The Nguyen-Widrow method can only be applied to layers
• With a bias
• With weights whose weightFcn is dotprod
• With netInputFcn set to netsum
• With transferFcn whose active region is finite

If these conditions are not met, then initnw uses rands to initialize the layer's weights and biases.

See Also

initwb, initlay, init

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