Geodesic
Nonlinear signal reconstruction based on the decomposition into chaotic components
Journal of computational and engineering mathematics, Tome 4 (2017) no. 4, pp. 29-37

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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. 
@article{JCEM_2017_4_4_a2,
     author = {A. S. Sheludko},
     title = {Nonlinear signal reconstruction based on the decomposition into chaotic components},
     journal = {Journal of computational and engineering mathematics},
     pages = {29--37},
     publisher = {mathdoc},
     volume = {4},
     number = {4},
     year = {2017},
     language = {en},
     url = {http://geodesic.mathdoc.fr/item/JCEM_2017_4_4_a2/}
}
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A. S. Sheludko. Nonlinear signal reconstruction based on the decomposition into chaotic components. Journal of computational and engineering mathematics, Tome 4 (2017) no. 4, pp. 29-37. http://geodesic.mathdoc.fr/item/JCEM_2017_4_4_a2/