Journal ArticleDOI
Robust Wiener filters
Saleem A. Kassam,Tong Leong Lim +1 more
TLDR
It is shown by a numerical example that the robust filter can be very useful in maintaining a reasonable error performance over the whole of the classes of PSD's.Abstract:
The performance of minimum mean-square-error estimation filters for signals in additive noise can deteriorate considerably for deviations of the actual signal and noise power spectral densities (PSD's) from assumed, nominal densities. We consider two classes of PSD's which are useful models for the signal and noise when their PSD's are not precisely known. For these classes, robust filters which are saddlepoints for mean-square- error performance are derived. The robust filters achieve their worst performance for pairs of least-favorable signal and noise PSD's for which they are the optimum filters. It is shown by a numerical example that the robust filter can be very useful in maintaining a reasonable error performance over the whole of the classes of PSD's.read more
Citations
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Journal ArticleDOI
Robust techniques for signal processing: A survey
Saleem A. Kassam,H.V. Poor +1 more
TL;DR: The minimax approach for the design of robust methods for signal processing is discussed, which has proven to be a very useful approach because it leads to constructive procedures for designing robust schemes.
Journal ArticleDOI
On minimax robustness: A general approach and applications
Sergio Verdu,H.V. Poor +1 more
TL;DR: It is shown that if the performance functional and the uncertainty set are convex then a certain type of regularity condition on the functional is sufficient to ensure that the optimal strategy for a least favorable element of the uncertaintySet is minimax robust.
Journal ArticleDOI
A competitive minimax approach to robust estimation of random parameters
Yonina C. Eldar,Neri Merhav +1 more
TL;DR: The minimax regret approach can improve the performance over both the minimax MSE approach and a "plug in" approach, in which the estimator is chosen to be equal to the MMSE estimator with an estimated covariance matrix replacing the true unknown covariance.
Journal ArticleDOI
On robust wiener filtering
TL;DR: In this article, a minimax formulation for the problem of designing robust Wiener filters for the situation of uncertain signal and noise spectra is proposed, and several results relating to solutions to this formulation in terms of least-favorable spectral pairs are presented.
Journal ArticleDOI
Robust Beamforming via Worst-Case SINR Maximization
TL;DR: It is shown that with a general convex uncertainty model, the worst-case SINR maximization problem can be solved by using convex optimization, and the result allows us to handle more general uncertainty models than prior work using a special form of uncertainty model.
References
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Journal ArticleDOI
Asymptotically robust detection of a known signal in contaminated non-Gaussian noise
S. Kassam,J. Thomas +1 more
TL;DR: The sign detector is shown to be the asymptotically most robust detector when g(x) is a double-exponential density.
Journal ArticleDOI
Robust estimation of signal amplitude
TL;DR: Simulation results show that both the iterative limiter estimator (ILE) and the ILCE possess a high degree of robustness for seemingly mild, but potent, deviations from the Gaussian model.