Asymptotic analysis of an algorithm for identification of quantized AR time-series

TitleAsymptotic analysis of an algorithm for identification of quantized AR time-series
Publication TypeConference Paper
Year of Publication1995
AuthorsKrishnamurthy, V., and H. V. Poor
Conference NameAcoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Pagination2028 -2031 vol.3
Date Publishedmay.
Keywordsasymptotic analysis, asymptotic covariances, autoregressive processes, binary series estimation algorithm, central limit theorem, covariance analysis, Gaussian AR models, Gaussian auto-regressive time series, Gaussian processes, identification, interference (signal), one-bit quantized measurements, parameter estimate, parameter estimation, parameter estimation algorithm, quantisation (signal), quantized AR time-series, signal processing, time series

Krishnamurthy and Mareels presented a parameter estimation algorithm called the binary series estimation algorithm (BSEA) for Gaussian auto-regressive (AR) time series given 1-bit quantized noisy measurements. The present authors carry out an asymptotic analysis of the BSEA for Gaussian AR models. In particular, from a central limit theorem they obtain expressions for the asymptotic covariances of the parameter estimates. From this they: (1) Present an algorithm for estimating the order of an AR series from one-bit quantized measurements. (2) Theoretically they justify why BSEA can yield better estimates than the Yule-Walker methods in some cases


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