DocumentCode
2505826
Title
Parameter estimation of short-time multi-component signals using damped-amplitude & polynomial-frequency model
Author
Li, Z. ; Martin, N. ; Vieira, M. ; Gueguen, P.
Author_Institution
Dept. Images Signal, Gipsa-Lab., St. Martin d´´Hères, France
fYear
2011
fDate
28-30 June 2011
Firstpage
545
Lastpage
548
Abstract
This paper concerns the parameter estimation of multi-component damped oscillations having non-linear frequency. In this paper, the instantaneous frequency is approximated by polynomials while the amplitude is characterized by damped exponentials to connect directly to its physical interpretations. A maximum likelihood procedure is developed via an adaptive simulated annealing technique which helps to speed up the convergence. Results on simulated signals show that the proposed algorithm is more efficient than the algorithm based on polynomial amplitude models, and allows the estimation of damping coefficients over a very short time duration. Finally, the proposed algorithm is applied for characterizing the ambient vibrations of a building.
Keywords
damping; maximum likelihood estimation; oscillations; parameter estimation; polynomials; signal representation; simulated annealing; adaptive simulated annealing technique; ambient vibration; damped exponential; damped-amplitude model; damping coefficient estimation; instantaneous frequency; maximum likelihood procedure; multicomponent damped oscillation; nonlinear frequency; parameter estimation; polynomial amplitude model; polynomial-frequency model; short-time multicomponent signal; signal representation; Adaptation models; Damping; Estimation; Frequency modulation; Polynomials; Signal to noise ratio; Simulated annealing; Adaptive simulated annealing; Damped amplitude; Maximum likelihood; Polynomial phase signal; Time-frequency;
fLanguage
English
Publisher
ieee
Conference_Titel
Statistical Signal Processing Workshop (SSP), 2011 IEEE
Conference_Location
Nice
ISSN
pending
Print_ISBN
978-1-4577-0569-4
Type
conf
DOI
10.1109/SSP.2011.5967755
Filename
5967755
Link To Document