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Adaptive training of artificial neural network

DSpace at IIT Bombay

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Title Adaptive training of artificial neural network
 
Creator KHAPARDE, SA
PARNERKAR, A
HIREMATH, NS
SHESHAPRASAD, BJ
 
Subject backpropagation
feedforward neural nets
optimisation
power system harmonics
 
Description 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.
 
Publisher IEEE
 
Date 2008-12-10T06:35:27Z
2011-11-28T08:20:12Z
2011-12-15T09:57:32Z
2008-12-10T06:35:27Z
2011-11-28T08:20:12Z
2011-12-15T09:57:32Z
1992
 
Type Article
 
Identifier 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
0-7803-0849-2
10.1109/TENCON.1992.272004
http://hdl.handle.net/10054/251
http://dspace.library.iitb.ac.in/xmlui/handle/10054/251
 
Language en