DocumentCode :
3234111
Title :
On-line adaptive estimation of symbol period
Author :
Doroslovaeki, M. ; Yao, Lei
Author_Institution :
Dept. of Electr. Eng. & Comput. Sci., George Washington Univ., Washington, DC, USA
Volume :
3
fYear :
1997
fDate :
2-5 Nov 1997
Firstpage :
1117
Abstract :
The application of the least-mean-square (LMS) and recursive-least-square (RLS) algorithms to the estimation of symbol period is discussed. The algorithms are based on the measurement of the time between two consecutive detected transitions in noisy waveforms. Two versions of the algorithm are developed for white and colored measurement noise models. Conditions are derived that guarantee proper behavior, i.e. the convergence, of the LMS and RLS algorithms. Simulation results show the convergence of algorithms and compare the algorithms with respect to convergence speed
Keywords :
adaptive estimation; convergence of numerical methods; least mean squares methods; recursive estimation; signal detection; white noise; LMS algorithm; RLS algorithm; colored noise; convergence speed; digitally modulated waveform detection; least-mean-square; measurement noise model; noisy waveforms; on-line adaptive estimation; recursive-least-square; simulation results; symbol period; time measurement; white noise; Adaptive estimation; Autocorrelation; Colored noise; Computer aided software engineering; Integrated circuit noise; Mean square error methods; Noise measurement; Random sequences; Stochastic resonance; White noise;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
MILCOM 97 Proceedings
Conference_Location :
Monterey, CA
Print_ISBN :
0-7803-4249-6
Type :
conf
DOI :
10.1109/MILCOM.1997.644873
Filename :
644873
Link To Document :
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