This paper introduces an approach to detect period information from motion capture data in low dimension. After a motion capture data is obtained, PCA method is utilized for dimension reduction. The accumulation contr...
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This paper introduces an approach to detect period information from motion capture data in low dimension. After a motion capture data is obtained, PCA method is utilized for dimension reduction. The accumulation contribution factor is used to determine the analysis dimension. Then the algorithm outputs the period through the low dimension computation. The method is assessed on CMU motion capture database and compared the performance of the automatic methods to that of manually selection. The results show that it has good characteristic for both simple and complex motions. This method can be used for motion database management and motion synthesization.
Multi-carrier (MC) CDMA technique can reduce the interference and improve the performance of the system in fading channel. But the frequency offset and multiple access interference (MAI) are obstructive to its perform...
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Multi-carrier (MC) CDMA technique can reduce the interference and improve the performance of the system in fading channel. But the frequency offset and multiple access interference (MAI) are obstructive to its performance. In this paper, combining the PIC multiuser detection and frequency offset estimation based on maximum likelihood function guard interval, we propose a joint detection which called M-ML-MPIC (modified maximum likelihood multistage parallel interference canceller) to correction the frequency offset and MAI simultaneously. The numerical results of the performance analysis and comparisons of conventional schemes with the proposed method are given.
Bilevel decision addresses the problem in which two levels of decision makers, each tries to optimize their individual objectives under constraints, act and react in an uncooperative, sequential manner. Such a bilevel...
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ISBN:
(纸本)9781920682309
Bilevel decision addresses the problem in which two levels of decision makers, each tries to optimize their individual objectives under constraints, act and react in an uncooperative, sequential manner. Such a bilevel optimization structure appears naturally in many aspects of planning, management and policy making. However, bilevel decision making may involve many uncertain factors in a real world problem. Therefore it is hard to determine the objective functions and constraints of the leader and the follower when build a bilevel decision model. To deal with this issue, this study explores the use of rule sets to format a bilevel decision problem by establishing a rule sets based model. After develop a method to construct a rule sets based bilevel model of a real-world problem, an example to illustrate the construction process is presented.
Web services composition techniques are gaining momentum as the opportunity to establish reusable and versatile inter-operability applications. Many researchers propose their composition approach based on planning tec...
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Web services composition techniques are gaining momentum as the opportunity to establish reusable and versatile inter-operability applications. Many researchers propose their composition approach based on planning techniques. We propose our context aware planning method which comprises global planning and local optimization based on context information. The major technical contributions of this paper are: (1) we propose an ontology-based framework for the context-aware composition of Web services. Context model, which are structured based on OWL-S, captures the service-related, environment-related, and user-related context and can be used in an unambiguous, machine interpretable form. (2) We propose context-aware plan architecture and thus is more scalability and flexibility for the planning process, and thereby improving the efficiency and precision. (3) We propose a hybrid approach to build a plan corresponding to a context-aware service composition, based on global planning and local optimization, considering both the usability and adoption. We test our approach on a simple, yet realistic example, and the preliminary results demonstrate that our implementation provides a practical solution
A method of single channel speech enhancement is proposed by de-noising using stationary wavelet transform. The approach developed herein processes multi-resolution wavelet coefficients individually and then recovery ...
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A method of single channel speech enhancement is proposed by de-noising using stationary wavelet transform. The approach developed herein processes multi-resolution wavelet coefficients individually and then recovery signal is reconstructed. The time invariant characteristics of stationary wavelet transform is particularly useful in speech de-noising. Experimental results show that the proposed speech enhancement by de-noising algorithm is possible to achieve an excellent balance between suppresses noise effectively and preserves as many target characteristics of original signal as possible. This de-noising algorithm offers a superior performance to speech signal noise suppress.
When the appearances of the tracked object and surrounding background change during tracking, fixed feature space tends to cause tracking failure. To address this problem, we propose a method to embed adaptive feature...
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A method of single channel speech enhancement is proposed by de-noising using stationary wavelet transform. The approach developed herein processes multi-resolution wavelet coefficients individually and then recovery ...
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A method of single channel speech enhancement is proposed by de-noising using stationary wavelet transform. The approach developed herein processes multi-resolution wavelet coefficients individually and then recovery signal is reconstructed. The time invariant characteristics of stationary wavelet transform is particularly useful in speech de-noising. Experimental results show that the proposed speech enhancement by de-noising algorithm is possible to achieve an excellent balance between suppresses noise effectively and preserves as many target characteristics of original signal as possible. This de-noising algorithm offers a superior performance to speech signal noise suppress.
A new scheme for approximating the solution of 2D Maxwell's equations using the symplectic scheme is introduced. The scheme is obtained by discretizing the Maxwell' s equations in the time direction based on s...
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A new scheme for approximating the solution of 2D Maxwell's equations using the symplectic scheme is introduced. The scheme is obtained by discretizing the Maxwell' s equations in the time direction based on symplectic scheme with different orders, and then evaluated the equation in the spatial direction with a second or fourth order finite difference approximation. The stability condition and numerical dispersion of the schemes with different orders are derived. The results are demonstrated by theoretical analysis and numerical simulation, the stability and numerical dispersion of the scheme with first and second order symplectic scheme (T1S2, T2S2) are identical to FDTD with a second order approximation in spatial direction. Although the high order schemes have almost the same stability as the FDTD, the fourth order scheme with a fourth order approximation in spatial direction (T4S4) has the superior numerical dispersion-isotropic properties of the scheme. Numerical results show that high order symplectic scheme is superior compared with FDTD for solving two-dimensional TMz case.
Label is denoted by disparity and the energy function is established. Then the problem of matching can be transformed into that of energy function minimization. A network is constructed such that the energies can be r...
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Label is denoted by disparity and the energy function is established. Then the problem of matching can be transformed into that of energy function minimization. A network is constructed such that the energies can be related to the capacities of the cuts of the network. Finally, the minimal energy is obtained by the network-flows theory, and hence the disparity data are solved. Comparing with some known algorithms based on graph cuts, the algorithm extends the label from 1 dimension vector to 2 dimension vector, and adapts vision matching of more general conditions;furthermore the algorithm can gain the minimization in global. Experimental results show that the algorithm has a high accuracy.
A novel and efficient speckle noise reduction algorithm based on Bayesian wavelet shrinkage using cycle spinning is proposed. First, the sub-band decompositions of non-logarithmically transformed SAR images are shown....
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A novel and efficient speckle noise reduction algorithm based on Bayesian wavelet shrinkage using cycle spinning is proposed. First, the sub-band decompositions of non-logarithmically transformed SAR images are shown. Then, a Bayesian wavelet shrinkage factor is applied to the decomposed data to estimate noise-free wavelet coefficients. The method is based on the Mixture Gaussian Distributed (MGD) modeling of sub-band coefficients. Finally, multi-resolution wavelet coefficients are reconstructed by wavelet-threshold using cycle spinning. Experimental results show that the proposed despeckling algorithm is possible to achieve an excellent balance between suppresses speckle effectively and preserves as many image details and sharpness as possible. The new method indicated its higher performance than the other speckle noise reduction techniques and minimizing the effect of pseudo-Gibbs phenomena.
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