The Experts below are selected from a list of 126525 Experts worldwide ranked by ideXlab platform
Judit Abardia - One of the best experts on this subject based on the ideXlab platform.
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minkowski valuations in a 2 dimensional Complex Vector space
International Mathematics Research Notices, 2015Co-Authors: Judit AbardiaAbstract:The classification of continuous, translation invariant Minkowski valuations which are contravariant (or covariant) with respect to the Complex special linear group is established in a 2-dimensional Complex Vector space. Every such valuation is given by the sum of a valuation of degree of homogeneity 1 and 3. In dimensions $m\geq 3$ such a classification was previously established and only valuations of a degree of homogeneity 2m-1 appear.
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Difference bodies in Complex Vector spaces
Journal of Functional Analysis, 2012Co-Authors: Judit AbardiaAbstract:Abstract A complete classification is obtained of continuous, translation invariant, Minkowski valuations on an m -dimensional Complex Vector space which are covariant under the Complex special linear group.
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Projection bodies in Complex Vector spaces
Advances in Mathematics, 2011Co-Authors: Judit Abardia, Andreas BernigAbstract:The space of Minkowski valuations on an m-dimensional Complex Vector space which are continuous, translation invariant and contravariant under the Complex special linear group is explicitly described. Each valuation with these properties is shown to satisfy geometric inequalities of the Brunn–Minkowski, Aleksandrov–Fenchel and Minkowski type.
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projection bodies in Complex Vector spaces
arXiv: Differential Geometry, 2011Co-Authors: Judit Abardia, Andreas BernigAbstract:The space of Minkowski valuations on an m-dimensional Complex Vector space which are continuous, translation invariant and contravariant under the Complex special linear group is explicitly described. Each valuation with these properties is shown to satisfy geometric inequalities of Brunn-Minkowski, Aleksandrov-Fenchel and Minkowski type.
Daniel C Ludois - One of the best experts on this subject based on the ideXlab platform.
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synchronous electrostatic machine torque modulation via Complex Vector voltage control with a current source inverter
IEEE Journal of Emerging and Selected Topics in Power Electronics, 2020Co-Authors: Aditya N Ghule, Peter Killeen, Daniel C LudoisAbstract:Advances in electrostatic machine design have enhanced the torque density of macroscale electrostatic machines toward practical use. A recently developed fractional horsepower three-phase separately excited synchronous electrostatic machine (SEM) demonstrates torque densities comparable to those of air-cooled permanent-magnet-based electromagnetic machines (1.5 Nm/kg) when excited with a medium voltage (5 kV). SEMs develop torque from voltage, not from current, and therefore incur nearly zero losses at low speeds or stall. However, there is no off-the-shelf medium-voltage drive at this power level, and the appropriate control framework for these machines has yet to be established. This article presents a Complex Vector voltage regulator control approach as a means for modulating torque in an SEM. Ampere-second (charge) is sourced from a current source inverter (CSI) serving as the drive electronics for voltage regulation. Together, the control approach and the CSI hardware form the first high-performance electrostatic drive. Key research outcomes include the theoretical development and experimental verification of charge-oriented control via voltage regulation. Experimental results are presented for rotational and stall conditions, which are reflective of the “position and hold” applications suited to electrostatic machines. The dynamic performance of the voltage regulator is verified by measuring the controller frequency response function, dynamic stiffness, and command tracking on a separately excited SEM.
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electrostatic machine drive using Complex Vector voltage regulation with a current source inverter platform
European Conference on Cognitive Ergonomics, 2018Co-Authors: Aditya N Ghule, Peter Killeen, Daniel C LudoisAbstract:Advancements in the torque capability of macroscale electrostatic machines prompts the development of controls and power electronics that are suitable to their radically different terminal characteristics and demonstrate performance in the context of canonical variable speed drives. Analysis of the separately excited electrostatic machine model indicates that a Complex Vector voltage regulator (CVVR) paired with a current sourced inverter (CSI) provides an intuitive solution to terminal voltage regulation and is a dual to magnetic drive systems utilizing voltage sourced inverters. Here, ampere-seconds (charge) is sourced by the CSI to the machine to modulate torque. Analysis of the voltage regulator for achieving high performance torque modulation is presented including transfer functions, command tracking and frequency response function plots. A kilowatt-scale medium-voltage (MV) CSI power electronic platform was developed as no off-the-shelf unit existed and the high pole count of electrostatic machines inherently requires high fundamental frequencies. A custom MV CSI unit was built by series stacking 3.6kV IGBTs with parallel snubbers (for static and dynamic balancing). The resulting drive is capable of synthesizing 5kV peak line-line with 5.5kHz PWM and may transition to six-step operation as the fundamental encroaches within an order of magnitude of the switching frequency.
Zhi Ding - One of the best experts on this subject based on the ideXlab platform.
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globally optimal linear precoders for finite alphabet signals over Complex Vector gaussian channels
IEEE Transactions on Signal Processing, 2011Co-Authors: Chengshan Xiao, Yahong Rosa Zheng, Zhi DingAbstract:We study the design optimization of linear precoders for maximizing the mutual information between finite alphabet input and the corresponding output over Complex-valued Vector channels. This mutual information is a nonlinear and non-concave function of the precoder parameters, posing a major obstacle to precoder design optimization. Our work presents three main contributions: First, we prove that the mutual information is a concave function of a matrix which itself is a quadratic function of the precoder matrix. Second, we propose a parameterized iterative algorithm for finding optimal linear precoders to achieve the global maximum of the mutual information. The proposed iterative algorithm is numerically robust, computationally efficient, and globally convergent. Third, we demonstrate that maximizing the mutual information between a discrete constellation input and the corresponding output of a Vector channel not only provides the highest practically achievable rate but also serves as an excellent criterion for minimizing the coded bit error rate. Our numerical examples show that the proposed algorithm achieves mutual information very close to the channel capacity for channel coding rate under 0.75, and also exhibits a large gain over existing linear precoding and/or power allocation algorithms. Moreover, our examples show that certain existing methods are susceptible to being trapped at locally optimal precoders.
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design optimization of linear precoders for Complex Vector gaussian channelswith finite alphabet inputs
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Chengshan Xiao, Yahong Rosa Zheng, Zhi DingAbstract:We study the design optimization of linear precoders that maximize the mutual information in Complex-valued Vector Gaussian channels under finite alphabet inputs. It is well known that mutual information of a Vector channel with discrete constellation source is a highly nonlinear and nonconcave function of the linear precoder matrix G, thereby complicating the precoder design optimization. In this paper, we show that the mutual information is a concave function of W = GhHhHG, where H is the Complex-valued channel matrix and superscript “h” represents conjugate transpose. We further propose an iterative algorithm for solving the globally optimal linear precoder G. Illustrative results show that the proposed iterative algorithm is very robust and efficient for global convergence.
Aditya N Ghule - One of the best experts on this subject based on the ideXlab platform.
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synchronous electrostatic machine torque modulation via Complex Vector voltage control with a current source inverter
IEEE Journal of Emerging and Selected Topics in Power Electronics, 2020Co-Authors: Aditya N Ghule, Peter Killeen, Daniel C LudoisAbstract:Advances in electrostatic machine design have enhanced the torque density of macroscale electrostatic machines toward practical use. A recently developed fractional horsepower three-phase separately excited synchronous electrostatic machine (SEM) demonstrates torque densities comparable to those of air-cooled permanent-magnet-based electromagnetic machines (1.5 Nm/kg) when excited with a medium voltage (5 kV). SEMs develop torque from voltage, not from current, and therefore incur nearly zero losses at low speeds or stall. However, there is no off-the-shelf medium-voltage drive at this power level, and the appropriate control framework for these machines has yet to be established. This article presents a Complex Vector voltage regulator control approach as a means for modulating torque in an SEM. Ampere-second (charge) is sourced from a current source inverter (CSI) serving as the drive electronics for voltage regulation. Together, the control approach and the CSI hardware form the first high-performance electrostatic drive. Key research outcomes include the theoretical development and experimental verification of charge-oriented control via voltage regulation. Experimental results are presented for rotational and stall conditions, which are reflective of the “position and hold” applications suited to electrostatic machines. The dynamic performance of the voltage regulator is verified by measuring the controller frequency response function, dynamic stiffness, and command tracking on a separately excited SEM.
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electrostatic machine drive using Complex Vector voltage regulation with a current source inverter platform
European Conference on Cognitive Ergonomics, 2018Co-Authors: Aditya N Ghule, Peter Killeen, Daniel C LudoisAbstract:Advancements in the torque capability of macroscale electrostatic machines prompts the development of controls and power electronics that are suitable to their radically different terminal characteristics and demonstrate performance in the context of canonical variable speed drives. Analysis of the separately excited electrostatic machine model indicates that a Complex Vector voltage regulator (CVVR) paired with a current sourced inverter (CSI) provides an intuitive solution to terminal voltage regulation and is a dual to magnetic drive systems utilizing voltage sourced inverters. Here, ampere-seconds (charge) is sourced by the CSI to the machine to modulate torque. Analysis of the voltage regulator for achieving high performance torque modulation is presented including transfer functions, command tracking and frequency response function plots. A kilowatt-scale medium-voltage (MV) CSI power electronic platform was developed as no off-the-shelf unit existed and the high pole count of electrostatic machines inherently requires high fundamental frequencies. A custom MV CSI unit was built by series stacking 3.6kV IGBTs with parallel snubbers (for static and dynamic balancing). The resulting drive is capable of synthesizing 5kV peak line-line with 5.5kHz PWM and may transition to six-step operation as the fundamental encroaches within an order of magnitude of the switching frequency.
Chengshan Xiao - One of the best experts on this subject based on the ideXlab platform.
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globally optimal linear precoders for finite alphabet signals over Complex Vector gaussian channels
IEEE Transactions on Signal Processing, 2011Co-Authors: Chengshan Xiao, Yahong Rosa Zheng, Zhi DingAbstract:We study the design optimization of linear precoders for maximizing the mutual information between finite alphabet input and the corresponding output over Complex-valued Vector channels. This mutual information is a nonlinear and non-concave function of the precoder parameters, posing a major obstacle to precoder design optimization. Our work presents three main contributions: First, we prove that the mutual information is a concave function of a matrix which itself is a quadratic function of the precoder matrix. Second, we propose a parameterized iterative algorithm for finding optimal linear precoders to achieve the global maximum of the mutual information. The proposed iterative algorithm is numerically robust, computationally efficient, and globally convergent. Third, we demonstrate that maximizing the mutual information between a discrete constellation input and the corresponding output of a Vector channel not only provides the highest practically achievable rate but also serves as an excellent criterion for minimizing the coded bit error rate. Our numerical examples show that the proposed algorithm achieves mutual information very close to the channel capacity for channel coding rate under 0.75, and also exhibits a large gain over existing linear precoding and/or power allocation algorithms. Moreover, our examples show that certain existing methods are susceptible to being trapped at locally optimal precoders.
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design optimization of linear precoders for Complex Vector gaussian channelswith finite alphabet inputs
International Conference on Acoustics Speech and Signal Processing, 2011Co-Authors: Chengshan Xiao, Yahong Rosa Zheng, Zhi DingAbstract:We study the design optimization of linear precoders that maximize the mutual information in Complex-valued Vector Gaussian channels under finite alphabet inputs. It is well known that mutual information of a Vector channel with discrete constellation source is a highly nonlinear and nonconcave function of the linear precoder matrix G, thereby complicating the precoder design optimization. In this paper, we show that the mutual information is a concave function of W = GhHhHG, where H is the Complex-valued channel matrix and superscript “h” represents conjugate transpose. We further propose an iterative algorithm for solving the globally optimal linear precoder G. Illustrative results show that the proposed iterative algorithm is very robust and efficient for global convergence.