DocumentCode :
3355303
Title :
Noise Reduction in Chaotic Signals by Using Wiener and Kalman Filtering Methods
Author :
Çek, Emre ; Oral, Ömer ; Akay, Olcay
Author_Institution :
Elektrik ve Elektron. Muhendisligi Bolumu, Izmir Yuksek Teknoloji Enstitusii, Izmir
fYear :
2007
fDate :
11-13 June 2007
Firstpage :
1
Lastpage :
4
Abstract :
In this paper, the additive white noise was filtered from chaotic signals obtained by logistic map by using Wiener, extended and unscented Kalman filters, respectively. Performances of each method were compared by finding mean square error versus signal to noise ratio (SNR) and correlation dimension which is one of the invariants of the chaotic dynamical systems. It was observed that, each method exhibits different MSE performances depending on the particular signal to noise ratio.
Keywords :
Kalman filters; Wiener filters; chaos; interference suppression; mean square error methods; Kalman filtering methods; SNR; Wiener filtering methods; additive white noise filtering; chaotic signals; correlation dimension; mean square error; noise reduction; signal-to noise ratio; Additive white noise; Chaos; Filtering; Kalman filters; Logistics; Mean square error methods; Noise reduction; Signal to noise ratio; Wiener filter;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signal Processing and Communications Applications, 2007. SIU 2007. IEEE 15th
Conference_Location :
Eskisehir
Print_ISBN :
1-4244-0719-2
Electronic_ISBN :
1-4244-0720-6
Type :
conf
DOI :
10.1109/SIU.2007.4298691
Filename :
4298691
Link To Document :
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