DocumentCode :
2802451
Title :
Adaptive ESPRIT algorithm based on the past subspace tracker
Author :
Badeau, Roland ; Richard, Guilhem ; David, Barak
Author_Institution :
Ecole Nat. Superieure des Telecommun., Paris, France
fYear :
2003
fDate :
19-22 Oct. 2003
Firstpage :
147
Abstract :
Summary form only given. Sinusoidal modeling is a powerful tool for audio signal processing, which represents the signal as a sum of sinusoids whose frequencies may vary over time. In most applications, the estimation and tracking of multiple frequencies is achieved by means of the Fourier analysis. Concurrently, we propose a new frequency estimation and tracking method, based on two algorithms derived from the concept of signal subspace. An application to audio is presented.
Keywords :
adaptive estimation; audio signal processing; frequency estimation; tracking; Fourier analysis; adaptive ESPRIT algorithm; adaptive estimation of signal parameters by rotational invariance techniques; audio signal processing; frequency estimation; multiple frequency tracking; signal parameter estimation; signal subspace; sinusoidal modeling; subspace tracker; Acoustic sensors; Computer networks; Distributed computing; Frequency synchronization; Particle filters; Position measurement; Sampling methods; Sensor arrays; Signal processing algorithms; Speech;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Applications of Signal Processing to Audio and Acoustics, 2003 IEEE Workshop on.
Print_ISBN :
0-7803-7850-4
Type :
conf
DOI :
10.1109/ASPAA.2003.1285843
Filename :
1285843
Link To Document :
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