Title :
Estimation of noisy quantized Gaussian AR time-series with randomly varying observation coefficient
Author :
Krishnamurthy, Vikram ; Mareels, Iven
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
fDate :
5/1/1995 12:00:00 AM
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
Keywords :
Gaussian noise; autoregressive processes; computational complexity; quantisation (signal); random processes; time series; white noise; Gaussian auto-regressive processes; estimation algorithm; multiplicative white Gaussian noise; noisy quantized Gaussian AR time-series; one-bit quantized observation sequences; ones; randomly varying observation coefficient; zeros; Australia; Gaussian noise; Linear systems; Maximum likelihood estimation; Nonlinear equations; Signal processing; Signal processing algorithms; Systems engineering and theory; Yttrium;
Journal_Title :
Signal Processing, IEEE Transactions on
