Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/61765
Title: Adaptive neural network for real-time estimation of basic waveforms of voltages and currents
Authors: Dash, P.K.
Patnaik, S.K.
Panda, S.K. 
Keywords: Adaptive neural network
Current
Real-time estimation
Voltage
Waveforms
Issue Date: 1996
Source: Dash, P.K.,Patnaik, S.K.,Panda, S.K. (1996). Adaptive neural network for real-time estimation of basic waveforms of voltages and currents. International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications 4 (1) : 33-42. ScholarBank@NUS Repository.
Abstract: A new algorithm for the estimation of parameters of voltage or current waveform of power networks contaminated by noise is proposed. The problem of estimation is formulated by using an adaptive neural network consisting of linear adaptive neurons called adaline. The learning parameters of the adaline are adjusted to force the error between the actual and desired outputs to satisfy a stable difference error equation, rather than to minimize an error function. Illustrative computer simulation results confirm the validity and accurate performance of the proposed method.
Source Title: International Journal of Engineering Intelligent Systems for Electrical Engineering and Communications
URI: http://scholarbank.nus.edu.sg/handle/10635/61765
ISSN: 09691170
Appears in Collections:Staff Publications

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