Title :
On some parameter estimation problems in alpha-stable processes
Author :
Swami, Ananthram
Author_Institution :
Army Res. Lab., Adelphi, MD, USA
Abstract :
Current algorithms for estimating the parameters of a symmetric alpha-stable ARMA process are either highly non-linear, or assume small MA orders (q⩽3), or invoke the minimum-phase assumption. We use results from the statistics literature to show that the normalized correlation is well-defined; we show that the normalized cumulants are also well-behaved. We propose to use the correlation to estimate the spectrally-equivalent minimum-phase (SEMP) parameters, and then to use the cumulants to resolve the phase of the model. We also show that correlation-based techniques (such as ESPRIT) work well for estimating the parameters of harmonics observed in alpha-stable noise. Correlation-based algorithms are shown to work well despite the infinite variance of the alpha-stable process
Keywords :
autoregressive moving average processes; correlation methods; harmonic analysis; higher order statistics; noise; numerical stability; phase estimation; spectral analysis; ESPRIT; algorithms; alpha-stable noise; convergence rates; correlation based algorithms; correlation based techniques; harmonics; infinite variance; minimum phase assumption; normalized correlation; normalized cumulants; parameter estimation; spectrally equivalent minimum phase parameters; statistics; symmetric alpha-stable ARMA process; Additive noise; Gaussian noise; Gaussian processes; Milling machines; Parameter estimation; Powders; Random variables; Signal processing algorithms; Signal resolution; Statistics;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1997. ICASSP-97., 1997 IEEE International Conference on
Conference_Location :
Munich
Print_ISBN :
0-8186-7919-0
DOI :
10.1109/ICASSP.1997.604630