This paper proposes a robust independent component analysis (ICA) approach for noise reduction. Noise reduction is a difficult problem in ICA. model. In general signal processing applications, there is more than one i...
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This paper proposes a robust independent component analysis (ICA) approach for noise reduction. Noise reduction is a difficult problem in ICA. model. In general signal processing applications, there is more than one interference signal which may have unknown characteristics. In these situations, traditional linear ICA may lead to poor results. Hence, noise reduction is preferred to be performed with nonlinear adaptive filtering. In this paper, a radial basis function network (RBFN) is employed to transform the observed signals into output space in a nonlinear manner. The weights of RBFN are updated by utilizing a modified fixed-pointalgorithm. The proposed method has not only the capacity of recovering the mixed signals, but also reducing noise with unknown characteristics from observed signals. The simulation results and analysis show that the proposed algorithm is suitable for practical unsupervised noise reduction problem. (C) 2008 Wiley Periodicals, Inc. Electron Comm Jpn, 91(3): 45-52, 2008;Published online in Wiley InterScience (***). DOI 10.1002/ecj.10073
This paper discusses the infinite horizon stochastic Nash games with state-dependent noise. After establishing the asymptotic structure along with the positive semidefiniteness for the solutions of the cross-coupled s...
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This paper discusses the infinite horizon stochastic Nash games with state-dependent noise. After establishing the asymptotic structure along with the positive semidefiniteness for the solutions of the cross-coupled stochastic algebraic Riccati equations (CSAREs), a new algorithm that combines Newton's method with two fixed point algorithms for solving the CSAREs is derived. As a result, it is shown that the proposed algorithm attains quadratic convergence and the reduced-order computations for sufficiently small parameter e. As another important feature, the high-order approximate strategy that is based on the iterative solutions is proposed. Using such strategy, the degradation of the cost functional is investigated. Finally, in order to demonstrate the efficiency of the proposed algorithms, computational examples are provided. (C) 2007 Elsevier Inc. All rights reserved.
In this paper, an algorithm for solving the algebraic Riccati equation (ARE) that has an indefinite sign quadratic term related to weakly coupled large-scale systems is investigated. A novel contribution is that a new...
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In this paper, an algorithm for solving the algebraic Riccati equation (ARE) that has an indefinite sign quadratic term related to weakly coupled large-scale systems is investigated. A novel contribution is that a new iterative algorithm is derived by combining Newton's method and the fixed point algorithm. As a result, for sufficiently small F, we can obtain an ARE solution with a quadratic convergence rate. Moreover, it is possible to calculate the ARE solution for the same dimension of each subsystem. As another important feature, an algorithm for solving the filter ARE is also discussed. Finally, in order to demonstrate the efficiency of the proposed algorithm, a numerical example is given. (C) 2007 Wiley Periodicals, Inc.
In this paper, a computational algorithm for solving sign-indefinite general multiparameter algebraic Riccati equation (SIGMARE) that arises in the H-infinity filtering problem is investigated. After establishing the ...
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In this paper, a computational algorithm for solving sign-indefinite general multiparameter algebraic Riccati equation (SIGMARE) that arises in the H-infinity filtering problem is investigated. After establishing the asymptotic structure of the solution of the SIGMARE, in order to solve the SIGMARE, Newton's method and two fixed point algorithms are combined. As a result, the new iterative algorithm achieves the quadratic convergence property and succeeds in reducing the computing workspace dramatically. As another important feature, the convergence criteria for small parameters epsilon(i) is derived for the first time. Moreover, it is shown that the uniqueness and positive semidefiniteness of the convergence solutions are guaranteed in the neighborhood of the initial conditions. (c) 2006 Elsevier Inc. All rights reserved.
In this paper, a new algorithm for solving cross-coupled sign-indefinite algebraic Riccati equations (CSAREs) for weakly coupled large-scale systems is proposed. It is shown that since the proposed algorithm is based ...
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In this paper, a new algorithm for solving cross-coupled sign-indefinite algebraic Riccati equations (CSAREs) for weakly coupled large-scale systems is proposed. It is shown that since the proposed algorithm is based on the Newton's method, the quadratic convergence is attained. Moreover, the local uniqueness of the convergence solutions for the CSAREs is investigated. Finally, in order to overcome the computation of large- and sparse-matrix related to the Newton's method, the fixed point algorithm and the alternating direction implicit (ADI) method are combined. (C) 2006 Elsevier Inc. All rights reserved.
A rigorous convergence analysis for the fixedpoint ICA algorithm of Hyvarinen and Oja is provided and a generalization of it involving cumulants of an arbitrary order is presented. We consider a specific optimization...
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A rigorous convergence analysis for the fixedpoint ICA algorithm of Hyvarinen and Oja is provided and a generalization of it involving cumulants of an arbitrary order is presented. We consider a specific optimization problem OP(p), p > 3, integer, arising from a Blind Source Extraction problem (BSE) and prove that every local maximum of OP(p) is a solution of (BSE) in sense that it extracts one source signal from a linear mixture of unknown statistically independent signals. An algorithm for solving OP(p) is constructed, which has a rate of convergence p - 1.
A rigorous convergence analysis for the fixedpoint ICA algorithm of Hyvarinen and Oja is provided and a generalization of it involving cumulants of an arbitrary order is presented. We consider a specific optimization...
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A rigorous convergence analysis for the fixedpoint ICA algorithm of Hyvarinen and Oja is provided and a generalization of it involving cumulants of an arbitrary order is presented. We consider a specific optimization problem OP(p), p > 3, integer, arising from a Blind Source Extraction problem (BSE) and prove that every local maximum of OP(p) is a solution of (BSE) in sense that it extracts one source signal from a linear mixture of unknown statistically independent signals. An algorithm for solving OP(p) is constructed, which has a rate of convergence p - 1.
The class of density based minimum distance estimators provide attractive alternatives to the maximum likelihood estimator because several members of this class have nice robustness properties while being first-order ...
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The class of density based minimum distance estimators provide attractive alternatives to the maximum likelihood estimator because several members of this class have nice robustness properties while being first-order efficient under the assumed model. A helpful computational technique-similar to the iteratively reweighted least squares used in robust regression-is introduced which makes these estimators computationally much more feasible. This technique is much simpler than the Newton-Raphson (NR) method to implement. The loss suffered in the rate of convergence compared to the NR method can be made to vanish in some exponential family situations by a little modification in the weight function-in which case the performance is comparable to the NR method. For a large number of parameters the performance of this modified version is actually expected to be better than the NR method. In view of the widespread interest in density based robust procedures, this modification appears to be of great practical value. (C) 2002 Elsevier B.V. All rights reserved.
In this paper, the linear quadratic N-players Nash games for infinite horizon large-scale systems are discussed. Nash strategies are obtained by solving the cross-coupled algebraic Riccati equations (CARE) via the num...
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ISBN:
(纸本)0780383354
In this paper, the linear quadratic N-players Nash games for infinite horizon large-scale systems are discussed. Nash strategies are obtained by solving the cross-coupled algebraic Riccati equations (CARE) via the numerical technique. The asymptotic expansions for the CARE are newly established. The main contribution in this paper is that the linear convergence of the proposed algorithm which is based on the fixed point algorithm is proved. In order to demonstrate the efficiency of the algorithm, numerical example is given for the practical power systems.
In this paper, H ∞ state feedback control for large-scale systems is investigated. The attention is focused on the design of the high-order approximate H ∞ controller which is based on the numerical solutions. The n...
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In this paper, H ∞ state feedback control for large-scale systems is investigated. The attention is focused on the design of the high-order approximate H ∞ controller which is based on the numerical solutions. The novel contribution is that a new iterative algorithm is derived by combining the Kleinman algorithm and the fixed point algorithm. As a result, H ∞ controller can be constructed in the same dimension of the subsystems. It is newly proved that the proposed algorithm has the quadratic convergence. Moreover, it is shown that the resulting controller achieves O(E 2 k ) approximation of the optimal H ∞ cost.
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