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Load prediction is a necessity in a deregulated electrical energy sector. It is important financially and technically. In order to cope with nonlinear and non stationary character of a load signal, an efficient adaptive predictor should be employed. Also, power utilities manage load information as a complex-valued signal. To this cause, performance of a class of complex-valued gradient descent (GD)...
The following topics are dealt with: neural networks for rehabilitation of sensory-motor systems; wind power forecast based on neural networks; neural adaptive FIR filters; and neural networks based signal processing.
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