Weight Initialisation for NN

Question

Can the weight initialization algorithm, known as the Nguyen-Widrow Algorithm, be used for a multi-layer perceptron neural network, which consists of more than one hidden layer? (like 6-4-4-3-2)

The paper which introduces this algorithm, only does it for a NN with one hidden layer. How can it be used for multi-hidden layers please?

Answer 1

The Nguyen-Widrow initialization algorithm is the following :

1. Initialize all weight of hidden layers with (ranged) random values
   
2. For each hidden layer
   2.1 calculate beta value, 0.7 * Nth(#neurons of input layer) root of #neurons of current layer
   2.2 for each synapse
   2.1.1 for each weight
   2.1.2 Adjust weight by dividing by norm of weight for neuron and multiplying by beta value

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