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|Title:||Adaptive training of artificial neural network|
Feedforward Neural Nets
Power System Harmonics
|Citation:||Tencon'92: Proceedings of the IEEE Region 10 International Conference on Technology Enabling Tomorrow : Computers, Communications and Automation towards the 21st Century (V 1), Melbourne, Australia, 11-13 November 1992, 525-529|
|Abstract:||Adaptive training of a neural network for nonstationary processes is reported within the framework of a multilayer perceptron model using the backpropagation (BP) algorithm. The error introduced by small changes in system parameters is reflected to adapt the changes in the converged weight matrix. The error is minimized using a constrained optimization method like the gradient projection method (GPM). The method is applied for harmonic prediction in voltage waveforms. The results for a sample system are discussed.|
|Appears in Collections:||Proceedings papers|
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