论文信息 - Implementing the optimal bounding ellipsoid algorithm on a fast processor

Implementing the optimal bounding ellipsoid algorithm on a fast processor

It is shown that the optimal bounding ellipsoid (OBE) algorithm for identifying an ARMAX system can be formulated as a conventional weighted recursive least squares estimator with special weights. In this framework the OBE can be implemented using contemporary algorithms developed for least squares solutions on systolic machines. An example of a systolic processor for OBE is given, and computational complexity issues are considered.<<ETX>>

John R. Deller | S. F. Odeh

[1] H. T. Kung,et al. Matrix Triangularization By Systolic Arrays , 1982, Optics & Photonics.

[2] J. R. Deller,et al. Linear prediction analysis of speech based on set-membership theory , 1989 .

[3] Y. F. Huang,et al. On the value of information in system identification - Bounded noise case , 1982, Autom..

[4] J. R. Deller,et al. Set-membership theory applied to linear prediction analysis of speech , 1987, ICASSP '87. IEEE International Conference on Acoustics, Speech, and Signal Processing.

[5] J. G. McWhirter,et al. Recursive Least-Squares Minimization Using A Systolic Array , 1983, Optics & Photonics.

[6] John R. Deller,et al. Advantages of a Givens rotation approach to temporally recursive linear prediction analysis of speech , 1989, IEEE Trans. Acoust. Speech Signal Process..

[7] W. E. Gentleman. Least Squares Computations by Givens Transformations Without Square Roots , 1973 .

[8] Yih-Fang Huang,et al. A recursive estimation algorithm using selective updating for spectral analysis and adaptive signal processing , 1986, IEEE Trans. Acoust. Speech Signal Process..

[9] J.R. Deller. A 'systolic array' formulation of the optimal bounding ellipsoid algorithm , 1989, IEEE Trans. Acoust. Speech Signal Process..