COMPLEX SIGNAL PREDICTION BASED ON DYNAMIC SYSTEM ALLOCATION LIMITS
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The paper proposes two methods for predicting complex signal, based on multilayer perceptron and SVM,
implemented in the software complex. The training set for the predictor is based on the allocation of border
implementations of dynamic systems in the signal.
Keywords: forecasting, change-point detection, fractal, dynamic systems, neural networks, SVM