DocumentCode :
3525462
Title :
On simulation of first-order auto-regressive processes with near Laplace marginals
Author :
Pawlak, Mirek ; Yahampath, Pradeepa
Author_Institution :
Dept. of Electr. & Comput. Eng., Univ. of Manitoba, Winnipeg, MB
fYear :
2009
fDate :
19-24 April 2009
Firstpage :
3421
Lastpage :
3424
Abstract :
The focus of this paper is the modeling of a class of stationary non-Gaussian auto-regressive processes that often find applications in statistical signal processing. We propose a general simulation procedure for constructing a time series model with a near-Laplace marginal distributions. Our approach is based on a class of Monte Carlo rejection algorithms. A theoretical analysis of the average complexity of the proposed algorithms for simulating the time series model is included.
Keywords :
Laplace equations; Monte Carlo methods; autoregressive processes; signal processing; statistical analysis; time series; Laplace marginal distribution; Monte Carlo rejection algorithm; stationary nonGaussian autoregressive process; statistical signal processing; time series model; Algorithm design and analysis; Analytical models; Computational modeling; Computer simulation; Density functional theory; Inverse problems; Monte Carlo methods; Signal processing algorithms; Speech analysis; Technological innovation; Laplace distribution; Monte Carlo; rejection algorithms; signal modeling; time series;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing, 2009. ICASSP 2009. IEEE International Conference on
Conference_Location :
Taipei
ISSN :
1520-6149
Print_ISBN :
978-1-4244-2353-8
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2009.4960360
Filename :
4960360
Link To Document :
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