Title :
A partitioned approach to spectral estimation
Author :
Rhodes, I. ; Constantinides, A.G.
Author_Institution :
Dept. of Electr. Eng., Imperial Coll. of Sci. & Technol., London, UK
Abstract :
In selecting a reduced parametric representation of a process, it is desirable to utilize any a priori knowledge available. The authors propose a general partitioning scheme that can utilize such knowledge in a local enhancement of the process model. By partitioning the observation space, or a transform thereof, into disjoint subspaces, alternative possibly conflicting constraints can be applied to each region. The optimal subspace partitioning is found using a dynamic programming algorithm minimizing a mean-least-square error criterion derived from a rational (ARMA) innovations model
Keywords :
filtering and prediction theory; spectral analysis; ARMA; dynamic programming; filtering; local enhancement; mean-least-square error criterion; observation space; partitioned approach; process model; spectral analysis; spectral estimation; subspaces; Covariance matrix; Dynamic programming; Educational institutions; Eigenvalues and eigenfunctions; Equations; Frequency estimation; Heuristic algorithms; Matrix decomposition; Signal processing; Space technology;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1989. ICASSP-89., 1989 International Conference on
Conference_Location :
Glasgow
DOI :
10.1109/ICASSP.1989.266933
