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检索条件"主题词=Algorithm Design And Analysis"

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Robot body design including degrees of freedom and link parameters maximizing ball throwing performance

Robot body design including degrees of freedom and link para...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Tetsuro Miyazaki Kazushi Sanada Department of Mechanical Engineering Yokohama National University Yokohama City Kanagawa 240-8501 Japan

ISBN: (纸本)9781509037636

This paper proposes a particular case of a robot body design method which determines a degrees of freedom (DOFs) number and link parameters to maximize a target task performance. The DOFs number is an essential point to be considered in the robot body design problem. In this paper, the target task is to make a long throw, and multi DOFs ball throwing robot is designed. design parameters are the robot body parameters and its motion pattern, and they are designed to maximize ball flying distance under long throw task conditions. To define the link lengths and the robot DOFs number as design parameters, it is assumed that intermediate links of the robot have identical actuators, and these link parameters are defined as functions of link lengths. These links are chained to construct the whole link system. Because of this assumption, the motion equation, which is utilized in the task conditions, is determined by the given robot DOFs number and link lengths. The proposed method was applied to the ball throwing robot model, and its body parameters and motion pattern were designed in the proposed calculation algorithm. As a result, 5 DOFs robot and its throwing motion were obtained, and the ball flying distance was maximized. The ball flying distance was changed along with the DOFs number, and the effectiveness of the proposed design method was demonstrated.

关键词： Mathematical model Acceleration Actuators design methodology Robot motion algorithm design and analysis

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Effective antenna pointing angle extraction of RPV SAR based on LTI analysis of image formation

Effective antenna pointing angle extraction of RPV SAR based...

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International Conference on Control, Instrumentation, and Automation

作者： Iman Heidarpour Shahrezaei Morteza Kazerooni Mohsen Fallah Department of electronic and electrical engineering Malek Ashtar University of Technology (MUT) Lavizan Tehran Iran

This paper, extracts optimum boundary antenna pointing angle which is proposed for Synthetic Aperture Radar (SAR) mounted on Remote Pilot Vehicle (RPV) platform. In traditional SAR systems, echo model directly applied to the algorithm and no systematic analysis on both other radar subsystems nor antenna pointing angle deviations were done. Comparison between proposed method and traditional SAR systems, Linear Time Invariant (LTI) model of RPV SAR subsystems is presented and effects of antenna pointing angle deviations on image formation algorithm is analyzed. Several calculations and LTI simulations of point target scatterer on range-Doppler algorithm demonstrate the validity of proposed method and boundary limitation extraction.

关键词： Synthetic aperture radar Linear systems Radar antennas algorithm design and analysis Doppler effect

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A new approach to Particle Swarm Optimization for dynamic systems with multiple units

A new approach to Particle Swarm Optimization for dynamic sy...

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Annual Conference of Industrial Electronics Society

作者： Frédéric Chassé Lyne Woodward Département de génie électrique Ecole de technologie supérieure Montréal Canada

Maximum Power Point Trackers (MPPT) are widely used to track in real-time the optimal power output of dynamic systems. These systems are sometimes comprised of multiple units which are similar, but not necessarily identical in terms of power curve and dynamics. A good example of such a system would be a photovoltaic (PV) array, which consists of multiple PV cells. Hence, it can be more profitable to operate each unit to its own optimal operating point instead of operating the whole system to a common optimal operating point. This paper proposes to use Particle Swarm Optimization (PSO) as an MPPT where each particle is assigned to a unit of a system. Although the method is validated both through simulations of a PV model and experimentations using a test bench of PV cells, it can be applied to many different dynamic systems comprising multiple units. The method proved to improve the convergence rate of the system and its total power production.

关键词： Optimization Particle swarm optimization Maximum power point trackers Convergence Heuristic algorithms Load modeling algorithm design and analysis

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A PTAS to minimize mobile sensor movement for target coverage problem

A PTAS to minimize mobile sensor movement for target coverag...

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IEEE Annual Joint Conference: INFOCOM, IEEE Computer and Communications Societies

作者： Zhiyin Chen Xiaofeng Gao Fan Wu Guihai Chen Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9781467399548

Energy consumption is a fundamental and critical issue in wireless sensor networks. Mobile sensors consume much more energy during the movement than that during the communication or sensing process. Thus how to schedule mobile sensors and minimize their moving distance has great significance to researchers. In this paper, we study the target coverage problem in mobile sensor networks. Our goal is to minimize the moving distance of sensors to cover all targets in the surveillance region. Here initially all the sensors are located at k base stations. Thus we define this problem as k-Sink Minimum Movement Target Coverage. To solve this problem, we propose a PTAS, named Energy Effective Movement algorithm (EEMA). We can divide EEMA into two phases. In the first phase, we partition the surveillance region into some subareas. In the second phase, we select subareas and schedule sensors to the selected subareas. We also prove that the approximation ratio of EEMA is 1 + ε and the time complexity is ηO(1/ε2 Finally, we conduct experiments to validate the efficiency and effectiveness of EEMA.

关键词： Mobile communication algorithm design and analysis Approximation algorithms Surveillance Heuristic algorithms Wireless sensor networks Mobile computing

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A Study on Path Planning of Unmanned Aerial Vehicle Based on Improved Genetic algorithm

A Study on Path Planning of Unmanned Aerial Vehicle Based on...

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International Conference on Intelligent Human-Machine Systems and Cybernetics, IHMSC

作者： Jihua Tao Chaoliang Zhong Li Gao Hao Deng School of Automation HangZhou DianZi University Hang Zhou

ISBN: (纸本)9781509007691

Genetic algorithm is a kind of way to solve complex problems effectively, for it is not bound by the restrictive assumptions of the search space, and doesn't require the assumption conditions such as continuity and derivatives. So this algorithm has its advantage that the traditional algorithm can not compared. Genetic algorithm uses multi-point search. In each iteration, the new individuals are generated by mating and mutation, so the searching range can be expanded, and the local optimal solution can be effectively prevented. In this paper, a real number encoding method based the change of course is proposed. According to the change of course, the algorithm constructs the individuality, and constructs the temporary path by the individual coding vector. And on this basis, the related operators shall be designed through the new encoding method and a series of genetic operations to carry out the path planning. The simulation results show that this method can improve the global search ability of genetic algorithm, and also improves the quality of Unmanned Aerial Vehicle flight path. The Unmanned Aerial Vehicle could get a better path in terms of the performance cost.

关键词： Encoding Genetic algorithms Path planning Unmanned aerial vehicles Biological cells Decoding algorithm design and analysis

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On performance improvement of the SOMA swarm based algorithm and its complex network duality

On performance improvement of the SOMA swarm based algorithm...

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Congress on Evolutionary Computation

作者： Lukas Tomaszek Ivan Zelinka Department of Computer Science FEI VSB Technical University of Ostrava Ostrava Czech Republic

ISBN: (纸本)9781509006243

In this participation, we are continuing in our research on swarm based algorithm SOMA - Self Organized Migrating algorithm and its use on problems defined in Competition track at WCCI 2016. In this paper we described SOMA algorithm, its conversion into complex network and we present modification called SOMARemove. Also we compare classical SOMA algoritm with SOMARemove on the first 8 functions of CEC15 benchmark in order to test the increase of the performance of new modification.

关键词： Sociology Statistics Cost function algorithm design and analysis Trajectory Complex networks

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Online nonnegative matrix factorization with outliers

Online nonnegative matrix factorization with outliers

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Renbo Zhao Vincent Y. F. Tan Department of Electrical and Computer Engineering National University of Singapore

ISBN: (纸本)9781479999897

We propose an optimization framework for performing online Non-negative Matrix Factorization (NMF) in the presence of outliers, based on l\ regularization and stochastic approximation. Due to the online nature of the algorithm, the proposed method has extremely low computational and storage complexity and is thus particularly applicable in this age of BigData. Furthermore, our algorithm shows promising performance in dealing with outliers, which previous online NMF algorithms fail to cope with. Convergence analysis shows the dictionary learned by our algorithm converges to that learned by its batch counterpart almost surely, as data size tends to infinity. We show numerically on a range of face datasets that our algorithm is superior to the state-of-the-art NMF algorithms in terms of running time, basis representations and reconstruction of original images. We also observe that our algorithm performs well even when the density of outliers reaches 40%. We provide explanations behind this seemingly surprising result.

关键词： algorithm design and analysis Optimization Dictionaries Clustering algorithms Face Approximation algorithms Convergence

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analysis dictionary learning for scene classification

Analysis dictionary learning for scene classification

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IEEE/SP Workshop on Statistical Signal Processing (SSP)

作者： Wen Tang Ives Rey Otero Hamid Krim Liyi Dai Department of Electrical and Computer Engineering North Carolina State University Raleigh NC USA Army Research Office RTP NC USA

ISBN: (纸本)9781467378048

This paper proposes a new framework for scene classification based on an analysis dictionary learning approach. Despite their tremendous success in various image processing tasks, synthesis-based and analysis-based sparse models fall short in classification tasks. It was hypothesized that this is partly due to the linear dependence of the dictionary atoms. In this work, we aim at improving classification performances by compensating for such dependence. The proposed methodology consists in grouping the atoms of the dictionary using clustering methods. This allows to sparsely model images from various scene classes and use such a model for classification. Experimental evidence shows the benefit of such an approach. Finally, we propose a supervised way to train the baseline representation for each class-specific dictionary, and achieve multiple classification by finding the minimum distance between the learned baseline representation and the data's sub-dictionary representation. Experiments seem to indicate that such approach achieves scene-classification performances that are comparable to the state of the art.

关键词： Dictionaries Sparse matrices Analytical models Minimization algorithm design and analysis Transforms Signal processing

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LEARNING DICTIONARIES FROM CORRELATED DATA: APPLICATION TO FMRI DATA analysis

LEARNING DICTIONARIES FROM CORRELATED DATA: APPLICATION TO F...

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IEEE International Conference on Image Processing

作者： Abd-Krim Seghouane Muhammad Usman Khalid Department of EEE Melbourne School of Engineering University of Melbourne Australia College of Engineering and Computer Science The Australian National University Canberra Australia

ISBN: (纸本)9781467399623

Sequential dictionary learning via the K-SVD algorithm has been revealed as a successful alternative to conventional data driven methods such as independent component analysis (ICA) for functional magnetic resonance imaging (fMRI) data analysis. fMRI data sets are however structured data matrices with notions of spatio-temporal correlation. This prior information has not been included in the K-SVD algorithm when applied in fMRI data analysis. In this paper we remedy to this situation by proposing a variant of the K-SVD algorithm dedicated to fMRI data analysis by taking into account this prior information. The proposed algorithm accounts for the known correlation structure in the fMRI data by using the squared Q, R-norm instead of the Frobenius norm for rank one approximation in the dictionary update stage. The performance of the proposed algorithm is illustrated through simulations and applications on a real fMRI data set.

关键词： Dictionaries Correlation Erbium Data analysis algorithm design and analysis Approximation algorithms Encoding

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Krill herd based clustering algorithm for wireless sensor networks

Krill herd based clustering algorithm for wireless sensor ne...

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International Workshop on Computational Intelligence (IWCI)

作者： Md. Shopon Md. Akhtaruzzaman Adnan Md. Firoz Mridha Department of Computer Science and Engineering University of Asia Pacific

ISBN: (纸本)9781509057702

Wireless sensor networks are principally categorized by insufficient energy resource. Naturally, communication between the nodes is the utmost energy consuming act that they perform. Hence, development of a well-organized clustering algorithm can play a vital part in enhancing the lifetime of network. Currently, nature inspired methodologies are very common in dealing with it. This work presents a centralized approach that deals with energy-awareness of wireless sensor networks using the Krill Herd algorithm. The performance of the suggested algorithm is assessed with famous clustering protocols. The simulation results show that suggested approach can maximize sensor network lifetime over other algorithms of the same category.

关键词： Clustering algorithms Wireless sensor networks Protocols algorithm design and analysis Base stations Scalability Mathematical model

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