Recursive autoregressive method for spectral estimation

A. Bouzerdoum; J. Kim

Recursive autoregressive method for spectral estimation

A. Bouzerdoum^*, J. Kim

^*Corresponding author for this work

University of Adelaide

Research output: Contribution to conference › Paper › peer-review

Abstract

In this article, we present a parametric technique for estimating the frequency of sinusoids in noise. The method is autoregressive where the AR model parameters are found by solving the normal equations recursively. The proposed method differs from existing ones in that only few iterations (one or two) are used to estimate the model parameters. This method, which we herein refer to as RAMSE is not sensitive to the model order, does not exhibit spectral line splitting and does not generate spurious peaks.

Original language	English
Pages	312-313
Number of pages	2
Publication status	Published - 1996
Externally published	Yes
Event	Proceedings of the 1996 4th International Symposium on Signal Processing and its Applications, ISSPA'96. Part 2 (of 2) - Gold Coast, Aust Duration: 25 Aug 1996 → 30 Aug 1996

Conference

Conference	Proceedings of the 1996 4th International Symposium on Signal Processing and its Applications, ISSPA'96. Part 2 (of 2)
City	Gold Coast, Aust
Period	25/08/96 → 30/08/96

Cite this

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title = "Recursive autoregressive method for spectral estimation",

abstract = "In this article, we present a parametric technique for estimating the frequency of sinusoids in noise. The method is autoregressive where the AR model parameters are found by solving the normal equations recursively. The proposed method differs from existing ones in that only few iterations (one or two) are used to estimate the model parameters. This method, which we herein refer to as RAMSE is not sensitive to the model order, does not exhibit spectral line splitting and does not generate spurious peaks.",

author = "A. Bouzerdoum and J. Kim",

year = "1996",

language = "English",

pages = "312--313",

note = "Proceedings of the 1996 4th International Symposium on Signal Processing and its Applications, ISSPA'96. Part 2 (of 2) ; Conference date: 25-08-1996 Through 30-08-1996",

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T1 - Recursive autoregressive method for spectral estimation

AU - Bouzerdoum, A.

AU - Kim, J.

PY - 1996

Y1 - 1996

N2 - In this article, we present a parametric technique for estimating the frequency of sinusoids in noise. The method is autoregressive where the AR model parameters are found by solving the normal equations recursively. The proposed method differs from existing ones in that only few iterations (one or two) are used to estimate the model parameters. This method, which we herein refer to as RAMSE is not sensitive to the model order, does not exhibit spectral line splitting and does not generate spurious peaks.

AB - In this article, we present a parametric technique for estimating the frequency of sinusoids in noise. The method is autoregressive where the AR model parameters are found by solving the normal equations recursively. The proposed method differs from existing ones in that only few iterations (one or two) are used to estimate the model parameters. This method, which we herein refer to as RAMSE is not sensitive to the model order, does not exhibit spectral line splitting and does not generate spurious peaks.

UR - http://www.scopus.com/inward/record.url?scp=0030357168&partnerID=8YFLogxK

M3 - Paper

AN - SCOPUS:0030357168

SP - 312

EP - 313

T2 - Proceedings of the 1996 4th International Symposium on Signal Processing and its Applications, ISSPA'96. Part 2 (of 2)

Y2 - 25 August 1996 through 30 August 1996

ER -

Recursive autoregressive method for spectral estimation

Abstract

Conference

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