Fast orthogonalization algorithm and parallel architecture for AR spectral estimation based on forward-backward linear prediction
Copyright policy )Fast orthogonalization algorithm and parallel architecture for AR spectral estimation based on forward-backward linear prediction
Truncated QR methods have been shown to be comparable to SVD-based methods for the sinusoidal frequency estimation based on the forward-backward linear prediction (FBLP) model. However, without exploiting the special structure of the FBLP matrix, the QR decomposition (QRD) of the FBLP matrix has a computational complexity on the order of 2(6m-n)n/sup 2//3+O(n/sup 2/) for a 2m*n FBLP matrix. A fast algorithm to perform the QRD of the FBLP matrix by exploiting its special Toeplitz-Hankel form is proposed. The computational complexity is reduced to 10n/sup 2/+4mn+O(n). The fast algorithm can also be easily implemented by a linear systolic array, reducing the number of time steps required to 2m+5n-4. >
- University of Maryland, College Park United States
- Systems Engineering Research Center United States
- University of Maryland, College Park United States
- National Chiao Tung University Taiwan
Estimation and detection in stochastic control theory, Inference from stochastic processes and spectral analysis
Estimation and detection in stochastic control theory, Inference from stochastic processes and spectral analysis
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