Vector control provides a fast torque response for motor control. In general, the vector control is used for the control of a rotary machine. In the case of the 3-degree-of-freedom (3-DOF) motor, the position of the r...
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Vector control provides a fast torque response for motor control. In general, the vector control is used for the control of a rotary machine. In the case of the 3-degree-of-freedom (3-DOF) motor, the position of the rotor is changed on three-dimensional space by tilting and rotating the motion of the shaft. Thus, when applying the vector control to the 3-DOF motor, the 3D co-ordinate transformation algorithm is required to decouple not only the field and torque current but the positioning (or tilting) current. The reliability of the proposed control algorithm was proven via experiments.
A new algorithm is presented for solving the nonlinear complementarity problem by combining the particle swarm and proximal point algorithm, which is called the particle swarm optimization-proximal point algorithm. Th...
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A new algorithm is presented for solving the nonlinear complementarity problem by combining the particle swarm and proximal point algorithm, which is called the particle swarm optimization-proximal point algorithm. The algorithm mainly transforms nonlinear complementarity problems into unconstrained optimization problems of smooth functions using the maximum entropy function and then optimizes the problem using the proximal point algorithm as the outer algorithm and particle swarm algorithm as the inner algorithm. The numerical results show that the algorithm has a fast convergence speed and good numerical stability, so it is an effective algorithm for solving nonlinear complementarity problems.
This paper presents a novel and uniform framework for face recognition. This framework is based on a combination of Gabor wavelets, direct linear discriminant analysis (DLDA) and support vector machine (SVM). First, f...
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This paper presents a novel and uniform framework for face recognition. This framework is based on a combination of Gabor wavelets, direct linear discriminant analysis (DLDA) and support vector machine (SVM). First, feature vectors are extracted from raw face images using Gabor wavelets. These Gabor-based features are robust against local distortions caused by the variance of illumination, expression and pose. Next, the extracted feature vectors are projected to a low-dimensional subspace using DLDA technique. The Gabor-based DLDA feature vectors are then applied to SVM classifier. A new kernel function for SVM called hyperhemispherically normalized polynomial (HNP) is also proposed in this paper and its validity on the improvement of classification accuracy is theoretically proved and experimentally tested for face recognition. The proposed algorithm was evaluated using the FERET database. Experimental results show that the proposed face recognition system outperforms other related approaches in terms of recognition rate. (C) 2012 Elsevier Ltd. All rights reserved.
In this paper, a wide-band scattering of one-dimensional (1-D) soil surface with exponential spectrum is investigated by the finite-difference time-domain (FDTD) algorithm with pulsed wave excitation. Soil is regarded...
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In this paper, a wide-band scattering of one-dimensional (1-D) soil surface with exponential spectrum is investigated by the finite-difference time-domain (FDTD) algorithm with pulsed wave excitation. Soil is regarded as isotropic and dispersive media, and it satisfies the two-pole Debye model. And the auxiliary differential equation (ADE) technique is incorporated into the FDTD scheme to deal with the dispersive soil. To ensure the validity of our present method, the wide-band scattering of dispersive soil surface by the ADE-FDTD method is computed and compared with the result by the conventional method of moments (MOM), which requires an individual calculation for every frequency point of interest. Finally, the scattering characteristic of dispersive soil surface is analyzed for different parameters in detail.
A novel concept for integrating visible light communications (VLC) with three-dimensional indoor positioning is presented. A VLC link based on transmitter and receiver characteristics using experimental measurements w...
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A novel concept for integrating visible light communications (VLC) with three-dimensional indoor positioning is presented. A VLC link based on transmitter and receiver characteristics using experimental measurements was modelled. Proposed is a three-dimensional positioning algorithm using received signal strength indication, which changes based on the angle and distance of the location based service. To reduce inter-cell interference, the transmitter's location code was sent using different subcarriers. A demonstration shows that the proposed algorithm can obtain a user's position, including height, accurately and without inter-cell interference.
The particle swarm optimization (PSO) algorithm superiority exists in convergence rate, but it tends to get stuck in local optima. An improved PSO algorithm is proposed using a best dimension mutation technique based ...
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The particle swarm optimization (PSO) algorithm superiority exists in convergence rate, but it tends to get stuck in local optima. An improved PSO algorithm is proposed using a best dimension mutation technique based on quantum theory, and it was applied to sensor scheduling problem for target tracking. The dynamics of the target are assumed as linear Gaussian model, and the sensor measurements show a linear correlation with the state of the target. This paper discusses the single target tracking problem with multiple sensors using the proposed best dimension mutation particle swarm optimization (BDMPSO) algorithm for various cases. Our experimental results verify that the proposed algorithm is able to track the target more reliably and accurately than previous ones.
In the paper, two-stage signal pre-processing algorithm based on the filtration is presented. The developed algorithm is dedicated for the diagnostic programmable device PUD-2. The PUD-2 is the real-time analyzer base...
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In the paper, two-stage signal pre-processing algorithm based on the filtration is presented. The developed algorithm is dedicated for the diagnostic programmable device PUD-2. The PUD-2 is the real-time analyzer based on programmable logic devices FPGA, as well as on ARM processor. Application of FPGA programmable devices and ARM processors allows to merge advantages of hardware and software implementations. Further, analysis of digital filters parameters in case of its efficient realization on the FPGA is presented. The aim of the study is to select digital-filter parameters in such way that the available resources of FPGA are used efficiently and filter characteristics meet established criteria. In the study, low pass finite impulse response and infinite impulse response filters are compared. For the first stage of the signal pre-processing algorithm, hardware implementation of the infinite impulse response filter is proposed, contrary to the second stage, where software realization of the finite impulse response filter is suggested. Combination of hardware and software filtration algorithms allows for fast and efficient realization of signal pre-processing algorithm used in analysis carried out on the PUD-2.
Image inpainting is a classical inverse problem of image science and has many applications. In the previous works, most of the variational inpainting methods can be considered as special cases of the restoration model...
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Image inpainting is a classical inverse problem of image science and has many applications. In the previous works, most of the variational inpainting methods can be considered as special cases of the restoration model where the linear operator is just the project to the known indexes. In this reported work, the variational inpainting model is established from the view of image decomposition. Then the unknown component can be recovered by the known component under the low-rank and joint-sparse constraints. Numerical experiments demonstrate that the proposed algorithm outperforms most of the current state-of-the-art methods with respect to the peak-signal-to-noise ratio value.
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