Abstract
Several methods have been suggested for estimating the parameters of an auto-regressive (AR) process where the innovation process is an independent, identically distributed (IID) α-stable process. The performance of the proposed algorithms has been studied by simulations. We suggest a novel, maximum likelihood (ML) type method for the same problem. Actually, we suggest use of the ML estimator for the Cauchy distribution for any 1 ≤ α <2. The performance of the proposed method is studied by simulations and its superiority over the existing methods is demonstrated. The simulations have been carried out carefully so the stationarity of the resulting AR process is guaranteed.
Original language | English |
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Title of host publication | Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
Pages | 237-240 |
Number of pages | 4 |
ISBN (Electronic) | 0769501400, 9780769501406 |
DOIs | |
State | Published - 1999 |
Externally published | Yes |
Event | 1999 IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999 - Caesarea, Israel Duration: 14 Jun 1999 → 16 Jun 1999 |
Publication series
Name | Proceedings of the IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999 |
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Conference
Conference | 1999 IEEE Signal Processing Workshop on Higher-Order Statistics, SPW-HOS 1999 |
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Country/Territory | Israel |
City | Caesarea |
Period | 14/06/99 → 16/06/99 |
Bibliographical note
Publisher Copyright:© 1999 IEEE.