Title :
Estimation of noisy quantized random observation coefficient AR time-series
Author :
Krishnamurthy, Vikram ; Mareels, I.M.Y.
Author_Institution :
Dept. of Syst. Eng., Australian Nat. Univ., Canberra, ACT, Australia
fDate :
27 Jun-1 Jul 1994
Abstract :
We present a consistent, asymptotically normal estimation algorithm for the parameters of auto-regressive (AR) processes from 1-bit quantized observations. The input signal to the quantifier is the AR signal corrupted by multiplicative white Gaussian noise. Our algorithm is computationally inexpensive as it involves counting the number of occurrences of particular patterns of zeros and ones in the observation sequence and then solving a Yule-Walker type system
Keywords :
Gaussian noise; autoregressive processes; parameter estimation; quantisation (signal); sequential estimation; time series; white noise; 1-bit quantized observations; AR signal; AR time-series; Yule-Walker type system; asymptotically normal estimation algorithm; auto-regressive processes; input signal; multiplicative white Gaussian noise; noisy quantized random observation coefficient; observation sequence; parameter estimation; Australia; Delta modulation; Equations; Gaussian noise; Signal processing; Speech analysis; Speech coding; Systems engineering and theory; Time series analysis; Yttrium;
Conference_Titel :
Information Theory, 1994. Proceedings., 1994 IEEE International Symposium on
Conference_Location :
Trondheim
Print_ISBN :
0-7803-2015-8
DOI :
10.1109/ISIT.1994.394873
