A modified backpropagation training algorithm for feedforward neural networks
T Kathirvalavakumar, P Thangavel - Neural Processing Letters, 2006 - Springer
Neural Processing Letters, 2006•Springer
In this paper, a new efficient learning procedure for training single hidden layer feedforward
network is proposed. This procedure trains the output layer and the hidden layer separately.
A new optimization criterion for the hidden layer is proposed. Existing methods to find
fictitious teacher signal for the output of each hidden neuron, modified standard
backpropagation algorithm and the new optimization criterion are combined to train the
feedforward neural networks. The effectiveness of the proposed procedure is shown by the …
network is proposed. This procedure trains the output layer and the hidden layer separately.
A new optimization criterion for the hidden layer is proposed. Existing methods to find
fictitious teacher signal for the output of each hidden neuron, modified standard
backpropagation algorithm and the new optimization criterion are combined to train the
feedforward neural networks. The effectiveness of the proposed procedure is shown by the …
Abstract
In this paper, a new efficient learning procedure for training single hidden layer feedforward network is proposed. This procedure trains the output layer and the hidden layer separately. A new optimization criterion for the hidden layer is proposed. Existing methods to find fictitious teacher signal for the output of each hidden neuron, modified standard backpropagation algorithm and the new optimization criterion are combined to train the feedforward neural networks. The effectiveness of the proposed procedure is shown by the simulation results.
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