[PDF] Top 20 Stochastic Behavior Analysis of the Gaussian Kernel Least-Mean-Square Algorithm
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Stochastic Behavior Analysis of the Gaussian Kernel Least-Mean-Square Algorithm
... Abstract—The kernel least-mean-square (KLMS) algorithm is a popular algorithm in nonlinear adaptive filtering due to its simplicity and ...In kernel adaptive ... Voir le document complet
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Stochastic Behavior Analysis of the Gaussian Kernel-Least-Mean-Square Algorithm
... Stochastic Behavior Analysis of the Gaussian Kernel Least-Mean-Square Algorithm Wemerson ...Abstract— The kernel ... Voir le document complet
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Gaussian kernel least-mean-square : design, analysis and applications
... address the problem of kernel selection, multikernel learning has been extensively studied in the literature for classification and regression [ Bach 2004 , Sonnenburg 2006 , Rakotomamonjy ... Voir le document complet
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Variants of non-negative least-mean-square algorithm and convergence analysis
... to the inherent physical characteristics of sys- tems under investigation, non-negativity is one of the most interesting constraints that can usually be imposed on the parameters to ... Voir le document complet
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Non-stationary Analysis of the Convergence of the Non-negative Least-mean-square Algorithm
... adaptive algorithm called Non-Negative Least Mean Square (NNLMS), which is suitable for online applications, has been proposed in ...on stochastic gradient de- scent approach combined ... Voir le document complet
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Mapping natural habitats using remote sensing and sparse partial least square discriminant analysis
... framework The method was implemented in an object-oriented image analysis ...Hence the first step of the method consisted in the segmentation of the remote sensing ... Voir le document complet
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Minimum mean square distance estimation of a subspace
... considered the problem of estimating a subspace using some available a priori ...where the subspace is assumed to be drawn from an appropriate prior ...manifold, the con- ventional MMSE ... Voir le document complet
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Mapping natural habitats using remote sensing and Sparse partial least square discriminant analysis
... Partial Least Square Discriminant Analysis This work presents a novel approach for mapping the spatial distribution of natural habitats in the “Foothills of Larzac” Natura ... Voir le document complet
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Dynamical behavior of a stochastic forward-backward algorithm using random monotone operators
... ], the functions g(ξ, . ) are supposed to have a full do- main, satisfy the inequality kg(ξ, x)−g(ξ, y)k ≤ L(kx−yk+1) for some constant L which does not depend on ξ and, finally, are such that R kg(ξ, x)k 2 ... Voir le document complet
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Least Square Approximations and Linear Values of Cooperative Game
... approximation of v by a game that induces an efficient value (the first equality) and, furthermore, preserves the total sum of the v(S) for some specific subsets (second ...are ... Voir le document complet
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Least Square Approximations and Conic Values of Cooperative Games
... Abstract The problem of least square approximation for set functions by set func- tions satisfying specified linear equality or inequality constraints is con- ...sidered. The problem ... Voir le document complet
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Hybridization of Differential evolution with Least-Square Support Vector Machines
... for the next gene- ration of Differential Evolution ...add the Least-Square Sup- port Vector Machine (LS-SVM) approximation in the end of each generation ...subset ... Voir le document complet
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Stochastic Analysis of the LMS Algorithm for System Identification with Subspace Inputs
... identifying the impulse response of a sparse ...(NEC). The advent of voice-over internet protocol (VoIP) [4] has revived interest in the NEC ...hundreds of echo cancellers for ... Voir le document complet
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Parallelization of the Gaussian Elimination Algorithm on Systolic Arrays
... L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignemen[r] ... Voir le document complet
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No-Mean Clustering Algorithm
... range of methods for cluster analysis. Each of these methods presenting pros and cons that are subject to the nature of the ...subjects: the k-means, and mixture ... Voir le document complet
81
On the root mean square quantitative chirality and quantitative symmetry measures
... for the degenerate triangle with only two equivalent vertices, which was cited in ...to the maximal value DSI ⫽1, for any dimension d⬎1. For d⫽2, the most chiral triangles also offer this remarkable ... Voir le document complet
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Simultaneous estimation of the mean and the variance in heteroscedastic Gaussian regression
... In the homoscedastic Gaussian framework with unknown variance, Akaike has proposed penalties for estimating the mean for quadratic risk (see [ 1 , 2 ] and [ 3 ...Replacing the variance ... Voir le document complet
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Simultaneous estimation of the mean and the variance in heteroscedastic Gaussian regression
... ǫ. The exponent α corresponds to the worst regularity between s and ...simultaneously the two functions, it is not paradoxical to obtain a rate of convergence that depends on the ... Voir le document complet
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Design of a power-scalable digital least-means-square adaptive filter
... In this thesis, we have used adaptive tap length and precision techniques to design a digital adaptive equalizer whose power consumption is scalable to the precision re[r] ... Voir le document complet
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Fréchet mean and p-mean on the unit circle: characterization, decidability, and algorithm
... Fréchet mean and generalizations. The celebrated center of mass of a point set P in a Euclidean space is the (a) point minimizing the sum of squared Euclidean to points in ... Voir le document complet
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