NONLINEAR SIGNAL RECONSTRUCTION BASED ON THE DECOMPOSITION INTO CHAOTIC COMPONENTS
Abstract
The paper proposes a signal reconstruction technique based on the decomposition into chaotic components. The considered approach can be usefully associated with the filtering, forecasting and control algorithms when only a small number of data samples is available. The developed decomposition algorithm involves sequential component extraction and recursive computation of the cost function. Some related questions are also discussed: choice of the class of chaotic maps, computational complexity of parameter estimation.
Keywords
signal reconstruction, chaotic map, parameter estimation, multiextremal cost function.
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