In many areas of pattern recognition and machine learning, subspace selection is an essential step. Fisher's linear discriminant analysis (LDA) is one of the most well-known linear subspace selection methods. Howe...
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Strategies for network immunization have been drawing wide interest in the area of complex networks during the past decade. The target strategy, in which degree values are used to determine vaccinating priority, has b...
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Evidence theory is widely used in many application systems such as information fusion and decision making under uncertainty environment. However, the classical Dempster combination rule is not efficient to deal with h...
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A group of decision-makers may differ in their choice of alternatives while making a decision. As a result, how to aggregate opinions of different experts is still an open issue. Due to the uncertainty in the process ...
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The PMCHWT equation of the double negative media (DNG) is obtained based on its constitutive relationship. And the surface currents and radar cross section (RCS) at a single frequency point is computed by Method of mo...
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Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition (EMD) algorithm and Teager energy operator (TEO) is proposed to locat...
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Accurate endpoint detection is a necessary capability for speech recognition. A new energy measure method based on the empirical mode decomposition (EMD) algorithm and Teager energy operator (TEO) is proposed to locate endpoint intervals of a speech signal embedded in noise. With the EMD, the noise signals can be decomposed into different numbers of sub-signals called intrinsic mode functions (IMFs), which is a zero-mean AM-FM component. Then TEO can be used to extract the desired feature of the modulation energy for IMF components. In order to show the effectiveness of the proposed method, examples are presented to show that the new measure is more effective than traditional measures. The present experimental results show that the measure can be used to improve the performance of endpoint detection algorithms and the accuracy of this algorithm is quite satisfactory and acceptable.
Secure Multi-party Computation (SMC) is a hot point concerning with information security and it is widely used in many fields, such as e-voting, e-auction and e-payment systems et al. This paper mainly discusses a spe...
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Secure Multi-party Computation (SMC) plays an important role in information security under the circumstance of cooperation calculation, so SMC on privacy-preservation is of great interest. In this paper we discuss an ...
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Ontology mapping is to find the mapping relationship between different ontology to reuse and share ontology. In this paper we present a multi-strategy ontology mapping technique based on the structure and instance. Wh...
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Particle swarm optimization (PSO) is a recently proposed population-based random search algorithm, which performs well in some optimization problems. In this paper, we proposed an improved PSO algorithm to solve portf...
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