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.
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%.
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.
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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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 moments (MOM). The asymptotic waveform evaluation (AWE) technique for dispersive dielectric medium is deduced and apllied to electromagnetic scattering analysis of double-negative medium within a given frequency band.
Based on illumination normalization and progressive thresholding, this paper presents a novel algorithm for automatic localization of human eyes in still images with complex background. First of all, Retinex method is...
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Based on illumination normalization and progressive thresholding, this paper presents a novel algorithm for automatic localization of human eyes in still images with complex background. First of all, Retinex method is used to realize normalizing of the face image. Secondly, a determination criterion of eye location is established by the priori knowledge of geometrical facial features. Thirdly, a range of threshold values that would separate eye blocks from others in a segmented face image is estimated. With the progressive increase of the threshold by an appropriate step in that range, once two eye blocks appear from the segmented image, they will be detected by the determination criterion of eye location. Finally, the 2-D correlation coefficient is used as a symmetry similarity measure to check the factuality of the two detected eyes. The experimental results demonstrate the high efficiency of the algorithm in runtime and correct localization rate.
Self-organizing networks (SON) for cellular systems are emerging as an important technology to reduce the cost of network deployment and maintenances. Mobility robustness optimization (MRO) is one of the main use case...
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Self-organizing networks (SON) for cellular systems are emerging as an important technology to reduce the cost of network deployment and maintenances. Mobility robustness optimization (MRO) is one of the main use cases of SON and has been intensively studied in 3GPP working groups. In this paper, we take the user equipment (UE) speed into account to solve the MRO problem. We propose a US-MRO algorithm, which assigns different Hysteresis parameters to UEs with different speed. The simulation results show that the success rate of Handover (HO) is improved and user experience is enhanced by the US-MRO algorithm.
A new incident source with different angles was constructed for dealing with wide-angle scattering problems. Considering the impendence matrix in method of moments (MOM) is independent from incident angles, the equiv...
A new incident source with different angles was constructed for dealing with wide-angle scattering problems. Considering the impendence matrix in method of moments (MOM) is independent from incident angles, the equivalent relationship between induced current and the measured CS-current was build, while the CS-current can be computed directly under the new incident source. Finally, we can reconstruct the induce current by utilizing the theory of compressive sensing (CS). Compared with traditional MOM, the computational complexity can be greatly reduced.
Randí et al. proposed a significant graphical representation for DNA sequences, which is very compact and avoids loss of information. In this paper, we build a fast algorithm for this graphical representation wit...
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A relative significance factor of an impact category is the external weight of the impact category and plays an important role in life cycle assessment(LCA). Many multiattribute decision-making (MADM) methods such as ...
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A relative significance factor of an impact category is the external weight of the impact category and plays an important role in life cycle assessment(LCA). Many multiattribute decision-making (MADM) methods such as analytical hierarchy process(AHP), the rank-order centroid method and the fuzzy method are proposed to determine the relative significance factor of an impact category. However, in previous research, it is shown that, the AHP approach is difficult for experts rendering consistent judgment when the number of pairwise comparisons increases, the rank-order method has some insurmountable shortcomings, the key issue to use fuzzy set theory is its complexity. In order to address this problem, a new simple and efficient method is proposed to determine relative significance factor in a more efficient manner. An example to determine relative significance factor of impact categories is shown to illustrate the efficiency of the proposed method.
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