Title :
Solution of the H∞ optimal linear filtering problem for discrete-time systems
Author :
Grimble, Michael J. ; El Sayed, Ahmed
Author_Institution :
Dept. of Electron. & Electr. Eng., Strathclyde Univ., Glasgow, UK
fDate :
7/1/1990 12:00:00 AM
Abstract :
The solution of l2 (minimum variance) and H∞ estimation problems is considered using a polynomial systems approach. The results for the l2 filtering problem, which corresponds with Wiener or Kalman filtering/prediction, are first presented in polynomial matrix form. Attention then turns to the solution of the H∞ estimation problem for scalar systems. Numerous examples are presented to illustrate the computational procedures. The two types of estimator are appropriate to very different estimation problems and the new H ∞ devices should be valuable in certain application areas
Keywords :
discrete time systems; estimation theory; filtering and prediction theory; polynomials; signal processing; H∞ estimation problem; Kalman filtering; Weiner filtering; discrete-time systems; l2 filtering problem; minimum variance estimation; optimal linear filtering problem; polynomial systems approach; prediction theory; scalar systems; signal processing; Equations; Estimation error; Filtering; Frequency estimation; H infinity control; Kalman filters; Maximum likelihood detection; Nonlinear filters; Polynomials; Wiener filter;
Journal_Title :
Acoustics, Speech and Signal Processing, IEEE Transactions on
