Estimation of noisy quantized Gaussian AR time-series with randomly varying observation coefficient

TitleEstimation of noisy quantized Gaussian AR time-series with randomly varying observation coefficient
Publication TypeJournal Article
Year of Publication1995
AuthorsKrishnamurthy, V., and I. Mareels
JournalSignal Processing, IEEE Transactions on
Volume43
Pagination1285 -1290
Date Publishedmay.
ISSN1053-587X
Keywordsautoregressive processes, computational complexity, estimation algorithm, Gaussian auto-regressive processes, Gaussian noise, multiplicative white Gaussian noise, noisy quantized Gaussian AR time-series, one-bit quantized observation sequences, ones, quantisation (signal), random processes, randomly varying observation coefficient, time series, white noise, zeros
Abstract

Presents an estimation algorithm for the parameters of Gaussian auto-regressive AR processes from one-bit quantized observation sequences. The input signal to the quantizer is the AR signal corrupted by multiplicative white Gaussian noise. The estimation algorithm is computationally inexpensive as it involves counting the number of occurrences of particular patterns of zeros and ones in the observation sequence

URLhttp://dx.doi.org/10.1109/78.382419
DOI10.1109/78.382419

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