Blind Extraction Of Chaotic Sources From White Gaussian Noise Based On A Measure Of Determinism

dc.creatorSoriano D.C.
dc.creatorSuyama R.
dc.creatorAttux R.
dc.date2009
dc.date2015-06-26T13:36:31Z
dc.date2015-11-26T15:36:32Z
dc.date2015-06-26T13:36:31Z
dc.date2015-11-26T15:36:32Z
dc.date.accessioned2018-03-28T22:45:02Z
dc.date.available2018-03-28T22:45:02Z
dc.identifier
dc.identifierLecture Notes In Computer Science (including Subseries Lecture Notes In Artificial Intelligence And Lecture Notes In Bioinformatics). , v. 5441, n. , p. 122 - 129, 2009.
dc.identifier3029743
dc.identifier10.1007/978-3-642-00599-2_16
dc.identifierhttp://www.scopus.com/inward/record.url?eid=2-s2.0-67149103768&partnerID=40&md5=89250780ed1411fe28984f63947c4e72
dc.identifierhttp://www.repositorio.unicamp.br/handle/REPOSIP/92570
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/92570
dc.identifier2-s2.0-67149103768
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1263461
dc.descriptionThis 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. © Springer-Verlag Berlin Heidelberg 2009.
dc.description5441
dc.description
dc.description122
dc.description129
dc.descriptionAbarbanel, D.I., (1996) Analysis of Observed Chaotic Data, , Springer, New York
dc.descriptionGrassberger, P., Procaccia, I., Measuring the strangeness of strange attractors (1983) Physica D, 9, pp. 189-208
dc.descriptionEckmann, J.-P., Kamphorst, S.O., Ruelle, D., Recurrence Plots of Dynamical Systems (1987) Europhysics Letters, 4, pp. 973-977
dc.descriptionLanda, P.S., Rosenblum, M.G., Time Series Analysis for System Identification and Diagnostics (1991) Physica D, 48, pp. 232-254
dc.descriptionBadii, R., Broggi, G., Derighetti, B., Ravani, M., Rubio, M.A., Dimension Increase in Filtered Chaotic Signals (1988) Physical Review Letters, 11, pp. 979-982
dc.descriptionKostelich, E.J., Schreiber, T., Noise reduction in chaotic time-series data: A survey of common methods (1993) Physical Review E, 48 (3), pp. 1752-1763
dc.descriptionMarwan, N., Romano, M.C., Thiel, M., Kurths, J., Recurrence plots for the analysis of complex systems (2007) Physics Reports, , 438, 237-329
dc.descriptionHyvarinen, A., Karhunen, J., Oja, E., (2001) Independent Component Analysis, , John Wiley & Sons, New-York
dc.descriptionHaykin, S., (2002) Adaptive Filter Theory, , Prentice Hall, New Jersey
dc.descriptionDarbellay, G.A., Vajda, I., Estimation of the Information by Adaptive Partitioning of the Observation Space (1999) IEEE Transactions on Information Theory, 45, pp. 1315-1321
dc.descriptionRohde, G.K., Nichols, J.M., Dissinger, B.M., Bucholtz, F., Stochastic analysis of recurrence plots with applications to the detection of deterministic signals (2008) Physica D, 237, pp. 619-629
dc.languageen
dc.publisher
dc.relationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
dc.rightsfechado
dc.sourceScopus
dc.titleBlind Extraction Of Chaotic Sources From White Gaussian Noise Based On A Measure Of Determinism
dc.typeActas de congresos


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