Oumar Diene

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The standard conjugate gradient (CG) method uses orthogonality of the residues to simplify the formulas for the parameters necessary for convergence. In adaptive filtering, the sample-by-sample update of the correlation matrix and the cross-correlation vector causes a loss of the residue orthogonality in a modified online algorithm, which, in turn, results(More)
Perceptrons, proposed in the seminal paper McCulloch-Pitts of 1943, have remained of interest to neural network community because of their simplicity and usefulness in classifying linearly separable data. Gradient descent and conjugate gradient are two widely used techniques for solving a set of linear inequalities. In finite precision implementation, the(More)
— Fault detection and isolation is an essential task in automated manufacturing systems and, as such, has received considerable attention in the literature. We propose in this paper a Petri net approach to online diagnosis of a discrete event system (DES) modeled by a finite state automaton. The diagnosis method requires, in general, less memory than other(More)
Multiuser mobile communication systems use linearly constrained adaptive filters for a blind adaptive interference cancelation and/or adaptive beamforming. Conjugate gradient (CG) techniques have been proposed, in the literature, for solving the adaptive filtering and the linearly constrained adaptive filtering problems. In adaptive filtering, the(More)