Adaptive ARMA Spectral Estimation,
Abstract
A novel adaptive method for efficiently obtaining an ARMA model spectral estimate of a wide-sense stationary time series is presented. It is adaptive in the sense that as a new element of the time series is observed, the coefficients of a (p,p)th order ARMA model may be algorithmically updated. This algorithm's computational complexity (i.e. the number of multiplications and additions required) is of the order p log(p) for a particular version of the method. Moreover, the spectral estimation performance of this new method is found typically to be far superior to such contemporary approaches as the Box-Jenkins, maximum entropy, and, Widrow's LMS methods. This performance in conjunction with its computational efficiency mark this algorithm as being a primary spectral estimation tool. (Author)
Document Details
- Document Type
- Technical Report
- Publication Date
- Jan 01, 1981
- Accession Number
- ADA098476
Entities
People
- James A. Cadzow
- Koji Ogino
Organizations
- Virginia Tech