The perturbed system with input-output dynamics of arbitrary and well defined relative degree is considered in a reduced information environment. The almost instantaneous convergence to the origin is achieved via impu...
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ISBN:
(纸本)9781467386838
The perturbed system with input-output dynamics of arbitrary and well defined relative degree is considered in a reduced information environment. The almost instantaneous convergence to the origin is achieved via impulsive control acting in a concert with continuous super-twisting controller. The impulsive actions are implemented in a piece-wise constant format. The efficacy of the proposed control algorithm is verified via simulations.
The storage energy of high frequency reactive component for the switched mode power converter is a new factor to assess the performance. The instability of the switched-mode converter under the peak current control mo...
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The storage energy of high frequency reactive component for the switched mode power converter is a new factor to assess the performance. The instability of the switched-mode converter under the peak current control mode is examined for its storage energy. Bifurcation and chaos of the storage energy in the inductor and capacitor are observed based on the stroboscopic map. The boundary of maximum storage energy is given to be an alternative to study the instability of the system in this study. Zero energy is obtained in stable period 1 and the storage energy with the same value and opposite direction is obtained in period 2. The simulation results of bifurcation and chaos of energy are obtained under different parameters and verified by experiment. The boundary of instability of energy stored in the reactive component under various parameters is formulated and a single equation can be used to indicate the factors. These results can provide a new guideline to design a stable system and provide a new control algorithm for power electronic system.
Extended discrete shearlet provides a directional multiresolution decomposition. It has been mathematically shown that extended discrete shearlet is a more efficient representation for the signals containing distribut...
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Extended discrete shearlet provides a directional multiresolution decomposition. It has been mathematically shown that extended discrete shearlet is a more efficient representation for the signals containing distributed discontinuities such as edges, compared to discrete wavelet. Multiresolution analyses such as curvelet and ridgelet share similar properties, yet their directional representations are significantly different from that of extended discrete shearlet. Taking advantage of the unique properties of directional representation of extended discrete shearlet, we develop an image watermark algorithm based on the largest information entropy. In proposed algorithm, firstly, 1-level extended discrete shearlet transform decomposes the test image into directional components on horizontal cone;each directional component reflects directional features and textured features differently. Next, the directional component whose information entropy is the highest is selected to carry watermark. Compared with related algorithms based on DWT and DCT, the proposed algorithm tends to obtain preferable invisibility when it is robust against common attacks.
It is a challenging task for a star sensor to implement star identification and determine the attitude of a spacecraft in the lost-in-space mode. Several algorithms based on triangle method are proposed for star ident...
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It is a challenging task for a star sensor to implement star identification and determine the attitude of a spacecraft in the lost-in-space mode. Several algorithms based on triangle method are proposed for star identification in this mode. However, these methods hold great time consumption and large guide star catalog memory size. The star identification performance of these methods requires improvements. To address these problems, a star identification algorithm using planar triangle principal component analysis is presented here. A star pattern is generated based on the planar triangle created by stars within the field of view of a star sensor and the projection of the triangle. Since a projection can determine an index for a unique triangle in the catalog, the adoption of the k-vector range search technique makes this algorithm very fast. In addition, a sharing star validation method is constructed to verify the identification results. Simulation results show that the proposed algorithm is more robust than the planar triangle and P-vector algorithms under the same conditions.
The local fractional Laplace variational iteration method (LFLVIM) is employed to handle the diffusion and wave equations on Cantor set. The operators are taken in the local sense. The nondifferentiable approximate so...
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The local fractional Laplace variational iteration method (LFLVIM) is employed to handle the diffusion and wave equations on Cantor set. The operators are taken in the local sense. The nondifferentiable approximate solutions are obtained by using the local fractional Laplace variational iteration method, which is the coupling method of local fractional variational iteration method and Laplace transform. Illustrative examples are included to demonstrate the high accuracy and fast convergence of this new algorithm.
The main objective of this letter is to improve the accuracy of unsupervised change detection method and minimize registration errors among multi-temporal images in the change detection process. To this end, iterative...
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The main objective of this letter is to improve the accuracy of unsupervised change detection method and minimize registration errors among multi-temporal images in the change detection process. To this end, iteratively regularized multivariate alteration detection (IR-MAD) is applied to synthetically fused images. First, four synthetically fused hyperspectral images are generated using the block-based fusion method. Then, the IR-MAD is applied to three pairs of the fused images using integrated IR-MAD variates, to decrease the falsely detected changes. To focus on the mis-registration effects, we apply the method to both a correctly registered data-set and a data-set with deliberately misaligned images. In this experiment using multi-temporal Hyperion images, the changed areas are more efficiently detected by our method than by the original IR-MAD algorithm.
Cartograms are used to visualize geographically distributed data by scaling the regions of a map (e.g., US states) such that their areas are proportional to some data associated with them (e.g., population). Thus the ...
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Cartograms are used to visualize geographically distributed data by scaling the regions of a map (e.g., US states) such that their areas are proportional to some data associated with them (e.g., population). Thus the cartogram computation problem can be considered as a map deformation problem where the input is a planar polygonal map M and an assignment of some positive weight for each region. The goal is to create a deformed map M, where the area of each region realizes the weight assigned to it (no cartographic error) while the overall map remains readable and recognizable (e.g., the topology, relative positions and shapes of the regions remain as close to those before the deformation as possible). Although several such measures of cartogram quality are well-known, different cartogram generation methods optimize different features and there is no standard set of quantitative metrics. In this paper we define such a set of seven quantitative measures, designed to evaluate how faithfully a cartogram represents the desired weights and to estimate the readability of the final representation. We then study several cartogram-generation algorithms and compare them in terms of these quantitative measures.
A description of a real algebraic variety in a"e(3) is given. This variety plays an important role in the investigation of the Einstein metrics whose evolution is studied using the normalized Ricci flow. To revea...
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A description of a real algebraic variety in a"e(3) is given. This variety plays an important role in the investigation of the Einstein metrics whose evolution is studied using the normalized Ricci flow. To reveal the internal structure of this variety, a description of all its singular points is given. Due to the internal symmetry of this variety, a part of the investigation uses elementary symmetric polynomials. All the computations are performed using computer algebra algorithms (in particular, Grobner bases) and algorithms for dealing with polynomial ideals. As an auxiliary result, a proposition about the structure of the discriminant surface of a cubic polynomial is proved.
We study how to utilize network coding to improve the throughput of secondary users (SUs) in cognitive radio networks (CRNs) when the channel quality is unavailable at SUs. We use a two-dimensional multiarmed bandit (...
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We study how to utilize network coding to improve the throughput of secondary users (SUs) in cognitive radio networks (CRNs) when the channel quality is unavailable at SUs. We use a two-dimensional multiarmed bandit (MAB) approach to solve the problem of SUs with network coding under unknown channel quality in CRNs. We analytically prove the asymptotical-throughput optimality of the proposed two-dimensional MAB algorithm. Simulation results show that our proposed algorithm achieves comparable throughput performance, compared to both the theoretical upper bound and the scheme assuming known channel quality information.
The consumption of conventional energy sources and environmental concerns have resulted in rapid growth in the amount of renewable energy introduced to power systems. With the help of distributed generations (DG), the...
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The consumption of conventional energy sources and environmental concerns have resulted in rapid growth in the amount of renewable energy introduced to power systems. With the help of distributed generations (DG), the improvement of power loss and voltage profile can be the salient benefits. However, studies show that improper placement and size of energy storage system (ESS) lead to undesired power loss and the risk of voltage stability, especially in the case of high renewable energy penetration. To solve the problem, this paper sets up a microgrid based on IEEE 34-bus distribution system which consists of wind power generation system, photovoltaic generation system, diesel generation system, and energy storage system associated with various types of load. Furthermore, the particle swarm optimization (PSO) algorithm is proposed in the paper to minimize the power loss and improve the system voltage profiles by optimally managing the different sorts of distributed generations under consideration of the worst condition of renewable energy production. The established IEEE 34-bus system is adopted to perform case studies. The detailed simulation results for each case clearly demonstrate the necessity of optimal management of the system operation and the effectiveness of the proposed method.
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