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Communications with chaotic time series: probabilistic methods for noise reduction

✍ Scribed by Dedieu, Hervé; Kisel, Andrey


Publisher
John Wiley and Sons
Year
1999
Tongue
English
Weight
130 KB
Volume
27
Category
Article
ISSN
0098-9886

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✦ Synopsis


The paper deals with noise decontamination of chaotic time series under the assumption that some a priori information about the system which produced the time series is known in advance. We show that this a priori information can be quite naturally used in standard maximum likelihood approaches. Focusing on low complexity implementations we derive di!erent quasioptimal maximum-likelihood solutions aimed at o!-line and on-line noise cleaning. The obtained results show attractive capabilities for on-line and low-cost implementation.