DocumentCode :
2310592
Title :
Optimal estimation for chaotic sequences using the Viterbi algorithm
Author :
Ciftci, Mahmut ; Williams, Douglas B.
Author_Institution :
Center for Signal & Image Process., Georgia Inst. of Technol., Atlanta, GA, USA
Volume :
2
fYear :
2001
fDate :
4-7 Nov. 2001
Firstpage :
1094
Abstract :
Many communications algorithms based on chaos have been proposed previously. However, the performance of these proposed algorithms has been limited by noise. In this paper, a novel, computationally efficient, optimal estimation algorithm for chaotic sequences is presented. First, a symbolic dynamics representation of the chaotic system is exploited to enable the representation of the chaotic dynamics by an equivalent trellis diagram. Then, the Viterbi algorithm is used to reduce the noise from the corrupted chaotic sequence. This algorithm yields the minimum mean square error estimate. The performance of the algorithm in terms of improvement versus signal-to-noise ratio (SNR) is simulated for popular chaotic maps, including sawtooth, tent, and logistic maps. The algorithm is also incorporated into a chaotic communication system, and the resulting bit-error rate (BER) performance is presented.
Keywords :
chaos; error statistics; least mean squares methods; maximum likelihood estimation; modulation; noise; optimisation; sequences; BER performance; SNR; Viterbi algorithm; bit-error rate; chaotic communication system; chaotic maps; chaotic modulation; chaotic sequences; communications algorithms; logistic map; minimum mean square error estimate; noise reduction; optimal estimation algorithm; sawtooth map; signal-to-noise ratio; symbolic dynamics representation; tent map; trellis diagram; Bit error rate; Chaos; Chaotic communication; Demodulation; Image processing; Maximum likelihood estimation; Noise reduction; Signal processing; Signal to noise ratio; Viterbi algorithm;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Signals, Systems and Computers, 2001. Conference Record of the Thirty-Fifth Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
ISSN :
1058-6393
Print_ISBN :
0-7803-7147-X
Type :
conf
DOI :
10.1109/ACSSC.2001.987662
Filename :
987662
Link To Document :
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