A Modified Backpropagation Training Algorithm for Feedforward Neural Networks
Neural Processing Letters
Identification and control for nonlinear discrete time systems using a new neural network
ISC '07 Proceedings of the 10th IASTED International Conference on Intelligent Systems and Control
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INES'09 Proceedings of the IEEE 13th international conference on Intelligent Engineering Systems
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A learning algorithm is presented for supervised learning of multilayered and interconnected neural networks without using a gradient method. First, fictitious teacher signals for the outputs of each hidden unit are algebraically determined by an error backpropagation (EBP) method. Then, the weight parameters are determined by using an exponentially weighted least squares (EWLS) method. This is called the EBP-EWLS algorithm for a multilayered neural network. For an interconnected neural network, the mathematical description of the neural network is arranged in the form for which the EBP-EWLS algorithm can be applied. Simulation studies have verified the proposed technique