Abstract
This work presents a new method to perform blind extraction of chaotic signals mixed with stochastic sources. The technique makes use of the features underlying the generation of chaotic sources to recover a signal that is “as deterministic as possible”. The method is applied to invertible and underdertemined mixture models and illustrates the potential of incorporating such a priori information about the nature of the sources in the process of blind extraction.
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Soriano, D.C., Suyama, R., Attux, R. (2009). Blind Extraction of Chaotic Sources from White Gaussian Noise Based on a Measure of Determinism. In: Adali, T., Jutten, C., Romano, J.M.T., Barros, A.K. (eds) Independent Component Analysis and Signal Separation. ICA 2009. Lecture Notes in Computer Science, vol 5441. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00599-2_16
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DOI: https://doi.org/10.1007/978-3-642-00599-2_16
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-00598-5
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