Title :
A comparison of five methods for computing the power spectrum of a random process using data segmentation
Author_Institution :
University of Tasmania, Hobart, Australia
fDate :
6/1/1977 12:00:00 AM
Abstract :
When we compute the power spectrum of a long input vector with limited core memory it is necessary to segment the data. Five alternative methods are possible. This paper presents a number of computed results comparing the resolution, stability, and overall quality of these methods.
Keywords :
Autocorrelation; Fast Fourier transforms; Filtering; Fourier transforms; Information science; Joining processes; Random number generation; Random processes; Stability; White noise;
Journal_Title :
Proceedings of the IEEE
DOI :
10.1109/PROC.1977.10600
