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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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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Locally linear embedding (LLE) is an elegant nonlinear method for feature extraction and manifold learning, which attempt to project the original data into a lower dimensional feature space by preserving the local nei...
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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 l...
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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.
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.
The existing data sampling schemes can not update ROM serial numbers of DS18B20 automatically and locate DS18B20s accurately. For these reasons above, it is difficult to replace the faulty DS18B20s immediately. To sol...
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The existing data sampling schemes can not update ROM serial numbers of DS18B20 automatically and locate DS18B20s accurately. For these reasons above, it is difficult to replace the faulty DS18B20s immediately. To solve this problem, both I/O (Input/Output) ports number of MCU (Micro Controller Unit) and the value of temperature alarm trigger registers (TH and TL) are used to determine the storage address of ROM serial numbers in 24LC256, and are also used to adopted as the physical address of DS18B20. Consequently, automatic updating of ROM (Read Only Memory) serial numbers and exactly locating of the temperature data can be completed. Meanwhile, to reduce the cost and avoid complex network cabling in wired network, a distributed wireless temperature and humidity monitoring system based on MCU and wireless networking is proposed.
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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According to defocus imaging theory, the amount of blur in the defocus images varies with depth of the object in the scene. So depth in the scene can be recovered by estimating the blur with the knowledge of the lens ...
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According to defocus imaging theory, the amount of blur in the defocus images varies with depth of the object in the scene. So depth in the scene can be recovered by estimating the blur with the knowledge of the lens parameters. A novel application of the total variation principle is made for the estimation of the amount of blur in the defocus images. Three main processes are included: the process of image defocusing is modeled using the model of anisotropic heat diffusion, then the depth recovery problem is translated into the minimum problem of energy functional with total variation regularization, and the gradient flow is used to seek the optimal solution. The recovery of focus image and the excess restrictions are avoided. The experiment results show that the algorithm is quite effective and depth information in edge is well retained particularly. Compared with the least square algorithm, depth recovery error with the total variation algorithm is reduced about 40%.
This study presents an efficient multi-resolution method to detect binary object directly. Both intensity and geometry differences are used to measure the similarity between the source object template and target objec...
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Recently, double-negative meta-materials are widely studied in scientific research. The double-negative (DNG) mediums are characterized by simultaneous negative permittivity and permeability. In order to make the FDTD...
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Recently, double-negative meta-materials are widely studied in scientific research. The double-negative (DNG) mediums are characterized by simultaneous negative permittivity and permeability. In order to make the FDTD method analyze the electromagnetic scattering and propagation for double-negative (DNG) medium, z-transform is applied to the FDTD method in the double-negative (DNG) medium. For the simulations, extremely large computer memory space and a long computational time b required. A parallel algorithm for the FDTD method on the state of the art graphics hardware is presented. The parallel computing techniques can be used to reduce the computation time significantly and have been widely applied in various complex FDTD applications. In this paper, we simulate the interaction between electromagnetic wave and DNG medium, and describe an impact of new GPU features on development process of an efficient Finite Difference Time Domain (FDTD) implementation.
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