The Experts below are selected from a list of 39177 Experts worldwide ranked by ideXlab platform
Lubo Li - One of the best experts on this subject based on the ideXlab platform.
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Multidimensional Space-Vector PWM Algorithm Using Branch Space Voltage Vector
IEEE Transactions on Power Electronics, 2016Co-Authors: Bin Li, Longji Li, Lubo LiAbstract:Typical algorithms of Multidimensional Space-vector pulsewidth modulation (SVPWM) divide (n -1) dimensional Space into (n-1)/2 subplanes with decoupling matrix or symmetrical component approach. However, the determination of effective sectors and appropriate Space voltage vectors takes a heavy computing burden. Taking the five-phase inverter as example, the relationship between the operation time of branch switches and the dwell times of active Space vectors in the SVPWM method is analyzed in this paper. Then, the branch Space voltage vector (BSVV) corresponding to the individual active branch voltage is defined and the synthesis of other active Space voltage vectors using BSVVs is given. Furthermore, only the BSVVs are chosen as the base vectors to synthesize the reference voltage vector, and a novel SVPWM algorithm is present. The operation time of branch switch is deduced, and the equivalence of the normalized load-phase voltages and operation times of branch switches is emphasized and used to analyze the simulation results. The zero-sequence voltage vector is also included in the algorithm as a parameter and its effects on the dwell time of the BSVVs, the modulation index and the common-mode voltage are explicated. Finally, the extension to an n-phase system is discussed. The algorithm eliminates the selection of sectors and proper active Space vectors, and can effectively control the dwell time of switches of multiphase inverter. Experimental results proved the feasibility and effectiveness of the algorithm.
Wen Hong - One of the best experts on this subject based on the ideXlab platform.
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Research progresss on Multidimensional Space joint-observation SAR
2015 40th International Conference on Infrared Millimeter and Terahertz waves (IRMMW-THz), 2015Co-Authors: Wen HongAbstract:With the application requirement and technology development, the necessity and tendency of Synthetic Aperture Radar (SAR) imaging within the framework of Multidimensional Space joint-observation, which are polarimetry, frequency, angle, time series and etc., evoke catholic interests in SAR imaging research nowadays. Recent research progress on the Multidimensional Space Joint-observation SAR (MSJosSAR) in the National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of, Sciences(MITL-IECAS) is reported in this talk, where the a sphere cluster cordinate system is defined as the modeling basis on the demand of information fusion for SAR Multidimensional Space joint-observation. Further more, the advantage of MSJosSAR is revealed by using Kronecker product decomposition for better understanding of target scattering mechanisms, with the hypothesis and basic framework on which the MSJosSAR signal processing relies on. Tentative studies on multi-layer material with PolinSAR technique, anisotropic scattering mechanisms with multi-directional observation (cuverture or circular SAR technique), and instantaneous time-variant target with array SAR technique are demonstrated as the initial verification of the above defined hypothesis and framework. Finally, the value of joint observation Space numbers for typical SAR configurations is enumerated, followed by the perspective discussions on the future work for MSJosSAR study.
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research progresss on Multidimensional Space joint observation sar
IEEE Asia-Pacific Conference on Synthetic Aperture Radar, 2013Co-Authors: Wen HongAbstract:With the application requirement and technology development, the necessity and tendency of Synthetic Aperture Radar (SAR) imaging within the framework of Multidimensional Space joint-observation, which are polarimetry, frequency, angle, time series and etc., evoke catholic interests in SAR imaging research nowadays. Recent research progress on the Multidimensional Space Joint-observation SAR (MSJosSAR) in the National Key Lab of Microwave Imaging Technology, Institute of Electronics, Chinese Academy of Sciences (MITL-IECAS) is reported in this talk, where the a sphere cluster coordinate system is defined as the modeling basis on the demand of information fusion for SAR Multidimensional Space joint-observation. Further more, the advantage of MSJosSAR is revealed by using Kronecker product decomposition for better understanding of target scattering mechanisms, with the hypothesis and basic framework on which the MSJosSAR signal processing relies on. Tentative studies on multi-layer material with PolinSAR technique, anisotropic scattering mechanisms with multi-directional observation (i.e. circular SAR technique), and instantaneous time-variant target with array SAR technique are demonstrated as the initial verification of the above defined hypothesis and framework. Finally, the value of joint observation Space numbers for typical SAR configurations is enumerated, followed by the perspective discussions on the future work for MSJosSAR study.
Anne Boyer - One of the best experts on this subject based on the ideXlab platform.
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Target tracking in the recommender Space: Toward a new recommender system based on Kalman filtering
2011Co-Authors: Samuel Nowakowski, Cédric Bernier, Anne BoyerAbstract:In this paper, we propose a new approach for recommender systems based on target tracking by Kalman filtering. We assume that users and their seen resources are vectors in the Multidimensional Space of the categories of the resources. Knowing this Space, we propose an algorithm based on a Kalman filter to track users and to predict the best prediction of their future position in the recommendation Space.
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Target Tracking in the recommender Space - Toward a new recommender system based on Kalman filtering
2011Co-Authors: Samuel Nowakowski, Anne Boyer, Bernier CédricAbstract:We assume that users and their consumptions of television programs are vectors in the Multidimensional Space of the categories of the resources. Knowing this Space, we propose an algorithm based on a Kalman filter to track the user's profile and to foresee the best prediction of their future position in the recommendation Space. From this prediction, we build a recommendation of contents.
Samuel Nowakowski - One of the best experts on this subject based on the ideXlab platform.
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Target tracking in the recommender Space: Toward a new recommender system based on Kalman filtering
2011Co-Authors: Samuel Nowakowski, Cédric Bernier, Anne BoyerAbstract:In this paper, we propose a new approach for recommender systems based on target tracking by Kalman filtering. We assume that users and their seen resources are vectors in the Multidimensional Space of the categories of the resources. Knowing this Space, we propose an algorithm based on a Kalman filter to track users and to predict the best prediction of their future position in the recommendation Space.
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Target Tracking in the recommender Space - Toward a new recommender system based on Kalman filtering
2011Co-Authors: Samuel Nowakowski, Anne Boyer, Bernier CédricAbstract:We assume that users and their consumptions of television programs are vectors in the Multidimensional Space of the categories of the resources. Knowing this Space, we propose an algorithm based on a Kalman filter to track the user's profile and to foresee the best prediction of their future position in the recommendation Space. From this prediction, we build a recommendation of contents.
Wenjie Zhang - One of the best experts on this subject based on the ideXlab platform.
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a unified approach for computing top k pairs in Multidimensional Space
International Conference on Data Engineering, 2011Co-Authors: Muhammad Aamir Cheema, Xuemin Lin, Haixun Wang, Jianmin Wang, Wenjie ZhangAbstract:Top-k pairs queries have many real applications. k closest pairs queries, k furthest pairs queries and their bichromatic variants are some of the examples of the top-k pairs queries that rank the pairs on distance functions. While these queries have received significant research attention, there does not exist a unified approach that can efficiently answer all these queries. Moreover, there is no existing work that supports top-k pairs queries based on generic scoring functions. In this paper, we present a unified approach that supports a broad class of top-k pairs queries including the queries mentioned above. Our proposed approach allows the users to define a local scoring function for each attribute involved in the query and a global scoring function that computes the final score of each pair by combining its scores on different attributes. We propose efficient internal and external memory algorithms and our theoretical analysis shows that the expected performance of the algorithms is optimal when two or less attributes are involved. Our approach does not require any pre-built indexes, is easy to implement and has low memory requirement. We conduct extensive experiments to demonstrate the efficiency of our proposed approach.
