Title :
The compressibility of stationary random processes
Author :
McCoy ; Magotra, J.W. ; Stearns, N.T.
Author_Institution :
Dept. of Electr. Eng. & Comput. Eng., New Mexico Univ., Albuquerque, NM
Abstract :
There are two types of inefficiencies in the time domain representation of a digitized random process. One is the time correlation between samples that causes one sample to be predictable based on the previous samples. Another is the non-uniform distribution of sample amplitudes. Maximum lossless compression of a stationary random process occurs when a sequence is completely decorrelated without loss and the decorrelated sequence is encoded at its entropy rate. This paper presents a mathematical description of theoretical limit of the compressibility of Gaussian stationary random processes
Keywords :
Gaussian processes; autoregressive moving average processes; correlation methods; data compression; encoding; entropy; random processes; signal representation; signal sampling; time-domain analysis; ARMA process; Gaussian stationary random processes; digitized random process; encoded decorrelated sequence; entropy rate; maximum lossless compression; nonuniform distribution; sample amplitudes; stationary random processes compressibility; time correlation; time domain representation; Decorrelation; Equations; Filtering; Filters; Linear systems; Noise level; Power generation; Power system modeling; Random processes; White noise;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
0-7803-3192-3
DOI :
10.1109/ICASSP.1996.547978
