In this paper, we investigate the self-adaptive source separation problem for convolutively mixed signals. The proposed approach uses a recurrent structure adapted by a generic rule involving arbitrary separating func...
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In this paper, we investigate the self-adaptive source separation problem for convolutively mixed signals. The proposed approach uses a recurrent structure adapted by a generic rule involving arbitrary separating functions. A stability analysis of this algorithm is first performed. It especially applies to some classical rules for instantaneous and convolutive mixtures that were proposed in the literature but only partly analysed, The expression of the asymptotic error variance is then determined for strictly causal mixtures. This enables to derive the optimum separating functions that minimize this error variance. They are shown to be only related to the probability density functions of the sources. To perform this error minimization, two normalization procedures that improve the algorithm properties are proposed. Their stability conditions and their asymptotic behaviour are analysed. (C) 1999 Elsevier Science B.V. All rights reserved.
Several exact linearization methods were applied to a simplified non-linear model for the concentration of dissolved oxygen in a waste water treatment plant, and digital control algorithms were derived based on these ...
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We consider a minimax resource allocation problem in which each term of the objective function is a strictly decreasing, invertible function of a single decision variable. The objective is to minimize the maximum term...
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We consider a minimax resource allocation problem in which each term of the objective function is a strictly decreasing, invertible function of a single decision variable. The objective is to minimize the maximum term subject to non-negativity constraints and a set of linear constraints with only non-negative parameters. We develop an algorithm that finds an optimal solution by repeatedly solving a relaxed minimax problem. In general, each relaxed problem is solved by simple search methods; however, for certain non-linear functions the algorithm employs closed form expressions.
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