REGULARIZED AUTOREGRESSIVE MULTIPLE FREQUENCY ESTIMATION

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CHEN BEI; GEL YULIA R.

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Paper Information

Journal: Journal of the Iranian Statistical Society Year:2011 | Volume:10 | Issue:2 Page(s): 141-166

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Information Journal Paper

Title

REGULARIZED AUTOREGRESSIVE MULTIPLE FREQUENCY ESTIMATION

Author(s)

CHEN BEI | GEL YULIA R. | Issue Writer Certificate

Keywords

AUTOREGRESSIVE APPROXIMATIONQ4

FREQUENCY TRACKINGQ4

LEAST SQUARES METHODQ4

PERIODIC TIME SERIESQ4

REGULARIZATIONQ4

Abstract

The paper addresses a problem of tracking multiple number of frequencies using Regularized Autoregressive (RAR) approximation. The RAR procedure allows to decrease approximation bias, comparing to other AR-based frequency detection methods, while still providing competitive variance of sample estimates. We show that the RAR estimates of multiple periodicities are consistent in probability and illustrate dynamics of RAR in respect to sample size and signal-to-noise ration by simulations.

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APA: Copy

CHEN, BEI, & GEL, YULIA R.. (2011). REGULARIZED AUTOREGRESSIVE MULTIPLE FREQUENCY ESTIMATION. JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS), 10(2), 141-166. SID. https://sid.ir/paper/117828/en

Vancouver: Copy

CHEN BEI, GEL YULIA R.. REGULARIZED AUTOREGRESSIVE MULTIPLE FREQUENCY ESTIMATION. JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS)[Internet]. 2011;10(2):141-166. Available from: https://sid.ir/paper/117828/en

IEEE: Copy

BEI CHEN, and YULIA R. GEL, “REGULARIZED AUTOREGRESSIVE MULTIPLE FREQUENCY ESTIMATION,” JOURNAL OF THE IRANIAN STATISTICAL SOCIETY (JIRSS), vol. 10, no. 2, pp. 141–166, 2011, [Online]. Available: https://sid.ir/paper/117828/en

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