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Orthonormal realization of fast fixed-order RLS adaptive filters

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Nonideal Sampling and Interpolation from Noisy Observations in Shift-Invariant Spaces

Michaël Unser

Digital analysis and processing of signals inherently relies on the existence of methods for reconstructing a continuous-time signal from a sequence of corrupted discrete-time samples. In this paper, a general formulation of this problem is developed that ...

IEEE2006

Mean-square performance of a convex combination of two adaptive filters

Ali H. Sayed

Combination approaches provide an interesting way to improve adaptive filter performance. In this paper, we study the mean-square performance of a convex combination of two transversal filters. The individual filters are independently adapted using their o ...

Institute of Electrical and Electronics Engineers2006

Classification-Specific Feature Sampling for Face Recognition

Pascal Frossard, Effrosyni Kokiopoulou

Feature extraction based on different types of signal filters has received a lot of attention in the context of face recognition. It generally results into extremely high dimensional feature vectors, and sampling of the coefficients is required to reduce t ...

2006

Tracking properties of a convex combination of two adaptive filters

Ali H. Sayed

Combination approaches provide a useful way to improve adaptive filter performance. In this paper, we study the tracking performance of an adaptive convex combination of two transversal filters. The individual filters are independently adapted using their ...

IEEE2005

A fast-array Kalman filter solution to active noise control

Ali H. Sayed

A Kalman filter solution to active control and its fast-array implementation are provided. The adaptive control problem is formulated as a state-estimation problem and no interchanging of the adaptive filter and the secondary-path is imposed. Moreover, no ...

Wiley Online Library2005

Extended fast fixed order RLS adaptive filters

Ali H. Sayed, Ricardo Merched

The existing derivations of conventional fast RLS adaptive filters are intrinsically dependent on the shift structure in the input regression vectors. This structure arises when a tapped-delay line (FIR) filter is used as a modeling filter. We show, unlike ...

IEEE2001

A framework for state-space estimation with uncertain models

Ali H. Sayed

Develops a framework for state-space estimation when the parameters of the underlying linear model are subject to uncertainties. Compared with existing robust filters, the proposed filters perform regularization rather than deregularization. It is shown th ...

Institute of Electrical and Electronics Engineers2001

An adaptive filter robust to data uncertainties

Ali H. Sayed

This paper considers the problem of adaptive filtering in the presence of uncertainties in the regression data. A recursive procedure is derived that is based on solving local optimization problems that attemps to alleviate the worst-case effect of data un ...

2000

Order-recursive RLS Laguerre adaptive filtering

Ali H. Sayed, Ricardo Merched

This paper solves the problem of designing recursive-least-squares (RLS) lattice (or order-recursive) algorithms for adaptive filters that do not involve tapped-delay-line structures. In particular, an RLS-Laguerre lattice filter is obtained. ...

IEEE2000

Exact RLS Laguerre-lattice adaptive filtering

Ali H. Sayed, Ricardo Merched

This paper solves the problem of designing an exact RLS lattice (or order-recursive) algorithms for adaptive filters that do not involve tapped-delay-line structures. As a special case, an exact RLS Laguerre lattice filter is obtained. ...

2000