A Contraction Mapping Approach for Robust Estimation of Lagged Autocorrelation

Seelamantula, Chandra Sekhar and Shenoy, Ravi R (2014) A Contraction Mapping Approach for Robust Estimation of Lagged Autocorrelation. In: IEEE SIGNAL PROCESSING LETTERS, 21 (9). pp. 1054-1058.

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Abstract

We consider the zero-crossing rate (ZCR) of a Gaussian process and establish a property relating the lagged ZCR (LZCR) to the corresponding normalized autocorrelation function. This is a generalization of Kedem's result for the lag-one case. For the specific case of a sinusoid in white Gaussian noise, we use the higher-order property between lagged ZCR and higher-lag autocorrelation to develop an iterative higher-order autoregressive filtering scheme, which stabilizes the ZCR and consequently provide robust estimates of the lagged autocorrelation. Simulation results show that the autocorrelation estimates converge in about 20 to 40 iterations even for low signal-to-noise ratio.

Item Type:	Journal Article
Publication:	IEEE SIGNAL PROCESSING LETTERS
Publisher:	IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Additional Information:	Copyright for this article belongs to the IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 445 HOES LANE, PISCATAWAY, NJ 08855-4141 USA
Keywords:	Contraction mapping; frequency estimation; lagged autocorrelation; lagged ZCR; zero-crossing rate (ZCR)
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	12 Jul 2014 15:06
Last Modified:	12 Jul 2014 15:06
URI:	http://eprints.iisc.ac.in/id/eprint/49400

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