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检索条件"主题词=Optimization algorithms"

共 4006 条记录，以下是2881-2890 订阅

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Digital Predistorter Identification based on Constrained Multi-Objective optimization of WLAN Standard Performance Metrics

Digital Predistorter Identification based on Constrained Mul...

引用

IEEE International Symposium on Circuits and Systems

作者： Karl Freiberger Martin Wolkerstorfer Harald Enzinger Christian Vogel FTW Telecommunications Research Center Vienna Donau-City-Strasse 1 A-1220 Vienna Austria FH Joanneum - University of Applied Sciences Austria and Graz University of Technology Austria

ISBN: (纸本)9781479983926

We present a new approach to identify the parameters of a given digital predistortion (DPD) structure for power amplifier (PA) linearization. Traditional methods optimize a single objective, typically the time-domain mean squared error. We propose to use a multi-objective optimization algorithm to jointly optimize the in-band and out-of-band performance as quantified by the respective metrics defined in the particular communication standard. Our constrained approach allows for checking standard-compliance at the time of DPD identification. Furthermore, the DPD model is not required to be linear in the parameters. We exemplify our approach with a WLAN simulation using a PA model at low back-off. By jointly optimizing the error vector magnitude (EVM) and spectral mask margin, we achieve significantly better results than the widely-used indirect learning architecture for the same memory polynomial DPD structure.

关键词： Communication standards standard performance predistorter optimization algorithms

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An Intrusion-Resilient Distributed optimization Algorithm for Modal Estimation in Power Systems 54th

An Intrusion-Resilient Distributed Optimization Algorithm fo...

引用

IEEE Annual Conference on Decision and Control

作者： Seyedbehzad Nabavi Aranya Chakrabortty Department of Electrical and Computer Engineering North Carolina State University Raleigh NC

ISBN: (纸本)9781479978878

In this paper we present an intrusion-resilient distributed algorithmic approach to estimate the electromechanical oscillation modes of a large power system using Synchrophasor measurements. For this, we first show how to distribute the centralized Prony method over a network consisting of several computational areas using a distributed variant of alternating direction method of multipliers (D-ADMM). We then add a cross-verification step to show the resiliency of this algorithm against the cyber-attacks that may happen in the form of data manipulation. We illustrate the robustness of our method in face of intrusion for a case study on IEEE 68-bus power system.

关键词： Distribute optimization algorithms algorithmic approach Case studies electromechanical oscillation data manipulation PRONY METHOD power systems HIGH POWER

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A proximal gradient algorithm for decentralized nondifferentiable optimization

A proximal gradient algorithm for decentralized nondifferent...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： W. Shi Q. Ling G. Wu W. Yin Dept. of Autom. Univ. of Sci. & Technol. of China Hefei China

ISBN: (纸本)9781467369985

In this paper, we focus on solving the decentralized consensus optimization problem defined over a networked multi-agent system. All the agents shall cooperatively find a common minimizer of the overall objective while each agent holds its own local objective and can only communicate with its neighbors. Motivated by many applications in which the local objective is the sum of a differentiable part and a nondifferentiable part, this paper proposes a proximal gradient exact first-order algorithm (PG-EXTRA) that utilizes the separable problem structure. Here, "exact" means this decentralized algorithm yields an exact consensus minimizer using a fixed step size. When the nondifferentiable part vanishes, PG-EXTRA reduces to EXTRA, an existing decentralized optimization algorithm. When the differentiable part vanishes, PG-EXTRA finds its special case P-EXTRA, a proximal algorithm. We prove convergence and rate of convergence for PG-EXTRA. Numerical experiments on a decentralized compressive sensing problem validates the theoretical results.

关键词： Multi-agent network decentralized optimization proximal gradient method Decentralized step size Converge Exact Differentiable Agents optimization algorithms

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optimization Algorithm for Home Energy Management System Based on Artificial Bee Colony in Smart Grid

Optimization Algorithm for Home Energy Management System Bas...

引用

IEEE International Conference on Cyber Technology in Automation, Control, and Intelligent Systems

作者： Yanyu Zhang Peng Zeng Chuanzhi Zang Key Lab. of Networked Control System Shenyang Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781479987313

To implement demand response in residential sector and facilitate the integration of renewable resources and plug-in electric vehicles in future smart grid, this paper proposes a framework of home energy management system (HEMS) and a optimization algorithm for it based on improved artificial bee colony. The algorithm schedules the operations of schedulable home appliances according to electricity price, forecasted outdoor temperature and renewable power output, and user preferences to minimize user's electricity cost. The effectiveness of the algorithm is verified by simulations, and the electricity cost can be reduced by 47.76%.

关键词： Smart grid Demand response Home energy management system Artificial bee colony optimization algorithm optimization algorithms Smart grids Demand-Responsive bee colonies Energy management systems Domestic architecture electricity costs Bee User preferences

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Local Smoothness in Variance Reduced optimization 15

Local Smoothness in Variance Reduced Optimization

引用

Annual Conference on Neural Information Processing Systems

作者： Daniel Vainsencher Han Liu Tong Zhang Dept. of Operations Research & Financial Engineering Princeton University Princeton NJ 08544 Dept. of Statistics Rutgers University Piscataway NJ 08854

ISBN: (纸本)9781510825024

We propose a family of non-uniform sampling strategies to provably speed up a class of stochastic optimization algorithms with linear convergence including Stochastic Variance Reduced Gradient (SVRG) and Stochastic Dual Coordinate Ascent (SDCA). For a large family of penalized empirical risk minimization problems, our methods exploit data dependent local smoothness of the loss functions near the optimum, while maintaining convergence guarantees. Our bounds are the first to quantify the advantage gained from local smoothness which are significant for some problems significantly better. Empirically, we provide thorough numerical results to back up our theory. Additionally we present algorithms exploiting local smoothness in more aggressive ways, which perform even better in practice.

关键词： Smoothness Variance optimization algorithms large family Stochastic

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A Review Paper on the Elimination of Harmonics in Multilevel Inverters using Bioinspired algorithms

A Review Paper on the Elimination of Harmonics in Multilevel...

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International Conference on Circuits, Power and Computing Technologies

作者： Teena Jacob L. Padma Suresh Dept. of EEE Noorul Islam University Kanyakumari District Tamil Nadu

ISBN: (纸本)9781509012787

Multilevel inverters are highly capable of achieving higher quality output voltage waveforms and higher power ratings with the help of their multilevel structure. They have been of great interest in the field of power industry and are best suited for reactive power compensation. Multilevel voltage source inverters are capable of operating at high voltagewith less electromagnetic interference and results in higher efficiency. The harmonic elimination in a multilevel voltage source inverter is of atmost importance and different types of modulation strategies can be applied to the inverters to eliminate these harmonics. Among these modulation techniques, Selective harmonic elimination PWM is asignificant switching strategy that can be applied to the output voltage waveform of multilevel inverters for lower order harmonic elimination. This paper gives a review on the various optimization algorithms that is been used for the SHEPWM technique. Performance comparisons of these optimization algorithms in SHEPWM are discussed.

关键词： Multilevel voltage source inverter Selective Harmonic Elimination Pulse Width Modulation (SHEPWM) optimization algorithms

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Butterworth Filter Design using Seeker optimization Algorithm

Butterworth Filter Design using Seeker Optimization Algorith...

引用

International Conference on Science and Technology

作者： K. B. Maji U. Soumika Sree R. Kar D. Mandal S. P. Ghoshal Department of Electronics and Communication Engg. NIT Department of Electrical Engineering NIT

ISBN: (纸本)9781467376716

In this work, fourth order Butterworth analog active low pass filter is reported by employing Seeker optimization Algorithm (SOA). The passive elements i.e. capacitors and resistors values are most important for the design of analog active low pass filter. Evolutionary optimization technique is used to select the values of capacitors and resistors for the design of fourth order Butterworth active low pass filter. In this algorithm, the search direction is based on empirical gradient by evaluating the response to the position changes and the step length is based on uncertainty reasoning by using a simple fuzzy rule. The circuit component values of the filter are chosen in such a way so that they become compatible with the industrial series E12. The simulation results prove that SOA is superior for the minimization of error existing in the designed circuit with respect to the reported works.

关键词： Evolutionary optimization Technique Seeker optimization Algorithm Analog active filter Butterworth filter Butterworth filters optimization algorithms changes position seekers Capacitors Resistor Device Component step size Service-oriented architecture Semiconductor Optical Amplifier Filters

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On the Convergence Rate of a Distributed Augmented Lagrangian optimization Algorithm

On the Convergence Rate of a Distributed Augmented Lagrangia...

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American Control Conference

作者： Nikolaos Chatzipanagiotis Michael M. Zavlanos Dept. of Mechanical Engineering and Materials Science Duke University Durham NC 27708 USA

ISBN: (纸本)9781479917730

We consider the Accelerated Distributed Augmented Lagrangians (ADAL) algorithm, a distributed optimization algorithm that was recently developed by the authors to address problems that involve multiple agents optimizing a separable convex objective function subject to convex local constraints and linear coupling constraints. optimization using augmented Lagrangians (AL) combines low computational complexity with fast convergence speeds due to the regularization terms included in the AL. However, decentralized methods that employ ALs are few, as decomposition of ALs is a particularly challenging task. ADAL is a primal-dual iterative scheme where at every iteration the agents locally optimize a novel separable approximation of the AL and then appropriately update their primal and dual variables, in a way that ensures convergence to their respective optimal sets. In this paper, we prove that ADAL has a worst-case O(1/k) convergence rate, where k denotes the number of iterations. The convergence rate is established in an ergodic sense, i.e., it refers to the ergodic average of the generated sequences of primal variables up to iteration k.

关键词： optimization algorithms Converge iterative methods Distribute complexity classes

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CORE: A Clustering optimization algorithm for Resource Efficiency in LTE-A Networks

CORE: A Clustering Optimization algorithm for Resource Effic...

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IEEE Global Communications Conference

作者： Georgios Kollias Ferran Adelantado Kostas Ramantas Christos Verikoukis Iquadrat Informatica Barcelona Universitat Oberta de Catalunya (UOC) Centre Tecnologic de Telecomunicacions de Catalunya (CTTC)

ISBN: (纸本)9781479959532

In a fluctuating mobile environment where operators have to confront the ever increasing demands of their subscribers, insufficient spectrum poses capacity limitations. This is more evident in the downlink (DL) direction, since DL resources are over-utilized compared to the uplink (UL) ones as a result of asymmetry in the generated traffic and intense interference. In this framework, we propose the creation of Device-to-Device (D2D) based clusters of users where intra-cluster communication will be achieved over UL resources. The minimization of the required resources (equivalent to the maximization of the spectral efficiency), is formulated as an integer (binary) linear optimization problem. Finally, a low-complexity clustering optimization algorithm for resource efficiency (CORE), is devised. Illustrative results prove that CORE, manages to increase the spectral efficiency and the network's capacity.

关键词： Device-to-Device communication LTE-A Asymmetry traffic Clustering Cluster Analysis core spectral efficiency optimization algorithms resource efficiency Generated traffic

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Consensus based Constrained optimization for Multi-agent Systems

Consensus based Constrained Optimization for Multi-agent Sys...

引用

IEEE Annual Conference on Decision and Control

作者： Shuai Liu Lihua Xie Cheng-Lin Liu School of EEE Nanyang Technological University Singapore Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi 214122 China

ISBN: (纸本)9781479978878

By introducing multi-agent systems, a consensus based distributed optimization algorithm is considered in this paper. The state of each agent is to be controlled to reach a consensus on the global optimal set. From control point of view, the control input of each agent is designed based on neighbours' state information and local cost functions. Necessary and sufficient conditions on the convergence of the whole system are given in terms of graph connectivity and balancedness, as well as the persistence of the decaying step size. The convergence rate is given under some general assumptions. Last, some numerical examples are given to show the effectiveness of the control protocol.

关键词： Constrained optimization control protocol control input optimization algorithms Agents control point step size Neighbor Converge Sufficient conditions based

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