Propose a new ensemble learning algorithm based on Fisher linear discriminant analysis (FLD or LDA) and Adaboost.M2 for multi-class classification problem. On each iteration of boosting, a number of bootstrap training...
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Propose a new ensemble learning algorithm based on Fisher linear discriminant analysis (FLD or LDA) and Adaboost.M2 for multi-class classification problem. On each iteration of boosting, a number of bootstrap training subsets are first sampled from the original training set according to the sample weights, and FLD is employed in each subset to construct a number of bootstrap FLD subspaces. Then the subspace with the minimum weighted K-nearest neighbor (KNN) pseudo-loss was selected to form the final strong classifier and update the sample weights. The main advantage of our algorithm is that its application is not restricted to the Gaussian assumption of data distribution, and the learning criterion is directly related to the minimum training error. Through the experiments on two real-world data sets, we demonstrate that our algorithm is superior to other techniques, especially for complex data distribution.
Stochastic approximation problem is to find some root or extremum of a nonlinear function for which only noisy measurements of the function are available. The classical algorithm for stochastic approximation problem i...
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Stochastic approximation problem is to find some root or extremum of a nonlinear function for which only noisy measurements of the function are available. The classical algorithm for stochastic approximation problem is the Robbins-Monro (RM) algorithm, which uses the noisy evaluation of the negative gradient direction as the iterative direction. In order to accelerate the RM algorithm, this paper gives a flame algorithm using adaptive iterative directions. At each iteration, the new algorithm goes towards either the noisy evaluation of the negative gradient direction or some other directions under some switch criterions. Two feasible choices of the criterions are proposed and two corresponding frame algorithms are formed. Different choices of the directions under the same given switch criterion in the frame can also form different algorithms. We also proposed the simultanous perturbation difference forms for the two frame algorithms. The almost surely convergence of the new algorithms are all established. The numerical experiments show that the new algorithms are promising.
In this paper,we study a posteriori error estimates of the edge stabilization Galerkin method for the constrained optimal control problem governed by convection-dominated diffusion *** residual-type a posteriori error...
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In this paper,we study a posteriori error estimates of the edge stabilization Galerkin method for the constrained optimal control problem governed by convection-dominated diffusion *** residual-type a posteriori error estimators yield both upper and lower bounds for control u measured in L2-norm and for state y and costate p measured in energy *** numerical examples are presented to illustrate the effectiveness of the error estimators provided in this paper.
In this paper the work on implementing two mesh partitioning algorithms, the refinement-tree based partitioning algorithm and the space-filling curve partitioning algorithm, in the parallel adaptive finite element too...
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In this paper the work on implementing two mesh partitioning algorithms, the refinement-tree based partitioning algorithm and the space-filling curve partitioning algorithm, in the parallel adaptive finite element toolbox PHG (parallel hierarchical grid) is presented. These algorithms are used for both initial mesh partitioning and mesh repartitioning for dynamical load balancing in adaptive finite element computations. In the implementations improved algorithms are designed. Partitioning time and quality of our code are compared with existing publicly available mesh or graph partitioners, including ParMETIS and Zoltan, through some numerical examples.
Objective image quality assessment (QA) is a fundamental and challenging job in image processing which evaluates the image quality consistently with human perception automatically. Generally, an image can be segmented...
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Objective image quality assessment (QA) is a fundamental and challenging job in image processing which evaluates the image quality consistently with human perception automatically. Generally, an image can be segmented into two kinds of areas: structure and texture. And structural information plays a much more important role between the two. The pixels, edges and shape with directional characteristic contribute much more to the structural information. In this paper, the structural information is modeled as the energy of directional projection, which is shown in a directional projection-based map that is built by Radon transform. On the assumption that any image's distortion could be modeled as the difference between the directional projection-based maps of reference and distortion images, we propose a new objective quality assessment method with Radon transform for full reference model, and we also try to explore the feasibility to develop the image QA metrics with scalable efficiency and computational cost. Experimental results show that the proposed metrics are well consistent with the subjective quality score.
PHG (parallel hierarchical grid) is a scalable parallel adaptive finite element toolbox under active developmentat the State keylaboratory of scientific and engineeringcomputing, Chinese Academy of Sciences. This pa...
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PHG (parallel hierarchical grid) is a scalable parallel adaptive finite element toolbox under active developmentat the State keylaboratory of scientific and engineeringcomputing, Chinese Academy of Sciences. This paper demonstrates its application to adaptive finite element computations of electromagnetic problems. Two examples on solving the time harmonic Maxwell's equations are shown. Results of some large scale adaptive finite element simulations with up to 1 billion degrees of freedom and using up to 2048 CPUs are presented.
Nowadays, digital images can be easily modified by using software. In this paper, a new blind approach is proposed to detect copy-paste trail in a doctored JPEG image, i.e., to check whether a copied area came from th...
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Nowadays, digital images can be easily modified by using software. In this paper, a new blind approach is proposed to detect copy-paste trail in a doctored JPEG image, i.e., to check whether a copied area came from the same image or not. When a copy-paste procedure is done on an image, especially adding or hiding an object, the block artifact grid contained in the copy-pasted slice is moved together. Since a slice must be placed properly in the target image to avoid obvious vision flaw, the grid in the slice mismatches to the original grid in the target image normally. Our approach utilizes the mismatch information of block artifact grid as a clue of copy-paste forgery. Experiment results demonstrate the efficiency of the proposed approach.
In this paper,we are concerned with the fast solvers for higher order edge finite element discretizations of Maxwell's *** present the preconditioners for the first family and second family of higher order N′ed′...
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In this paper,we are concerned with the fast solvers for higher order edge finite element discretizations of Maxwell's *** present the preconditioners for the first family and second family of higher order N′ed′elec element equations,*** combining the stable decompositions of two kinds of edge finite element spaces with the abstract theory of auxiliary space preconditioning,we prove that the corresponding condition numbers of our preconditioners are uniformly bounded on quasi-uniform *** also present some numerical experiments to demonstrate the theoretical results.
The traditional DCT-based real-valued discrete Gabor transform (RGDT) was limited to the critical sampling case. The biorthogonality relationship between the analysis window and the synthesis window for the transform ...
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The traditional DCT-based real-valued discrete Gabor transform (RGDT) was limited to the critical sampling case. The biorthogonality relationship between the analysis window and the synthesis window for the transform has not been unveiled. To overcome those drawbacks, this paper proposes a novel DCT-based real-valued discrete Gabor transform, which can be applied under both the critical sampling condition and the over-sampling condition. And the biorthogonality relationship between the analysis window and the synthesis window for the transform is also proved in this paper. Because it only involves real operations and can utilize fast DCT and DDCT algorithms for fast computation, it facilitates computation and implementation by hardware and/or software compared to the traditional complex-valued discrete Gabor transform.
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