Title :
A higher-order moment formula for non-zero-mean AR processes
Author :
Ngo, Chiu Yeung ; Mendel, Jerry M.
Author_Institution :
Dept. of Electr. Eng.-Syst., Univ. of Southern California, Los Angeles, CA, USA
Abstract :
An autoregressive (AR) model which is excited by a non-zero-mean, independent and identically distributed stationary random process is investigated. As in the zero-mean case, a cumulant-based higher-order Yule-Walker equation is derived. By expanding the cumulants in terms of their moments, a higher-order moment formula is obtained. This formula not only relates the higher-order moment with the lower-order moment, but also makes it possible to estimate the AR parameters and the output mean simultaneously. The formula is computationally more efficient than the cumulant formula
Keywords :
random processes; signal processing; statistical analysis; cumulant expansion; cumulant-based higher-order Yule-Walker equation; higher-order moment; identically distributed stationary random process; independent random process; lower-order moment; nonzero mean autoregressive processes; output mean; signal processing; statistical analysis; Additive white noise; Equations; Gaussian noise; Gaussian processes; Image processing; Integrated circuit modeling; Maximum likelihood estimation; Parameter estimation; Random processes; Signal processing;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1991. ICASSP-91., 1991 International Conference on
Conference_Location :
Toronto, Ont.
Print_ISBN :
0-7803-0003-3
DOI :
10.1109/ICASSP.1991.150108
