On unbiased parameter estimation of autoregressive signals observed in noise

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Abstract

In a recent paper, a simple least-squares (LS) based algorithm is introduced for unbiased parameter estimation of autoregressive (AR) signals observed in noise, under the assumption that the ratio between the driving source power and the corrupting noise variance is known. In the present paper, this LS based algorithm is modified with a more computationally efficient algorithmic structure. The mean convergence of the modified algorithm is then investigated. The issue of how the assumption of the known power ratio can be mitigated for practical applications is discussed, which leads to the development of an effective estimation algorithm for noisy AR signals. Theoretical results are validated through computer simulations.

Original languageEnglish
Pages (from-to)IV261-IV264
JournalProceedings - IEEE International Symposium on Circuits and Systems
Volume4
Publication statusPublished - 2003
EventProceedings of the 2003 IEEE International Symposium on Circuits and Systems - Bangkok, Thailand
Duration: 25 May 200328 May 2003

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