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检索条件"主题词=Pursuit Algorithms"

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Towards a learning automata solution to the multi-constraint partitioning problem

Towards a learning automata solution to the multi-constraint...

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IEEE Conference on Cybernetics and Intelligent Systems

作者： Horn, Geir Ommen, B. John SIMULA Res Lab POB 134 N-1325 Lysaker Norway Carleton Univ Sch Comp Sci Ottawa ON K1S 5B6 Canada

ISBN: (纸本)9781424400225

We consider the problem of partitioning a set of elements (or objects) into mutually exclusive classes (or groups), where elements which are "similar" to each other are, hopefully, located in the same class. This problem has been shown to be NP-Hard, and the literature reports solutions in which the similarity constraint consists of a single index. For example, typical "similarity" conditions that have been used in the literature include those in which "similar" objects are accessed together, or when they communicate (as processes do) with each other. In this paper, we present the first reported solution(1) to the case when the objects could be linked together in a multi-constraint manner, and indeed, visit the scenario when the constraints could, themselves, be contradictory. The solution we propose is based on the theory of estimator-based Learning Automata (LA), operating in non-stationary environments. Rather than use traditional estimates, we advocate the use of stochastic weak-estimates [2] and the specific digraph properties of the relations between the elements. Although the solutions proposed perform admirably when the number of elements is small, the simulated results demonstrate that the quality of the final solution decreases with the number of elements. Thus, although this is the first reported solution to the problem which incorporates specific digraph properties of the objects, the scalability of the solution remains open.

关键词： object partitioning multi-constraint partitioning learning automata pursuit algorithms

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Path Tracking using Vector pursuit Algorithm for Tracked Vehicles Driving on the Soft Cohesive Soil

Path Tracking using Vector Pursuit Algorithm for Tracked Veh...

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SICE Annual Conference

作者： Tae-kyeong Yeu Soung-jea Park Sup Hong Hyung-woo Kim Jong-su Choi Maritime & Ocean Engineering Research(MOERI) KORDI Daejeon South Korea

Generally, tracked vehicles are used in military, agricultural and recreational applications where terrain conditions are improper or unpredictable. Tracked vehicles are better than wheeled vehicles due to the larger contact area of tracks providing better floatation and traction at various ground conditions. In this paper, the path tracking method is proposed for tracked vehicle driving on the deep-sea soft cohesive soil. Firstly, to generate the vehicle's motion following the specified path, the vector pursuit algorithm is used. Next, to drive the vehicle as the generated motion, the control method based on the relation between the traction force and the track slip is proposed. Finally, to prove the performance of vector pursuit algorithm, the numerical simulation is done. Also, to directly induce the relation of traction force-slip, the draw-bar pull test is executed

关键词： pursuit algorithms Vehicle driving Soil Land vehicles Road vehicles Force control Motion control Tracking Numerical simulation Testing

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A Group Matching pursuit Algorithm for Sparse Channel Estimation for OFDM Transmission

A Group Matching Pursuit Algorithm for Sparse Channel Estima...

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

作者： Chun-Jung Wu D.W. Lin Department of Electronics Engineering and Center for Telecommunications Research National Chiao Tung University Hsinchu Taiwan

Time-domain channel estimation techniques have been proposed for OFDM systems for their ability to yield relatively accurate estimates with only a few pilots. Key information needed in such techniques is the multipath delays of the channel. Prior approaches to estimation of multipath delays require regular pilot structures and may not work in slow fading. We propose a group matching pursuit technique for channel estimation. The technique is an extension of the orthogonal matching pursuit technique. It employs the pilots in several OFDM symbols to estimate the multipath delays in a sequential manner, where the pilots can have an arbitrary structure. Simulation results show that the proposed algorithm has superior performance

关键词： Matching pursuit algorithms pursuit algorithms Channel estimation OFDM Delay estimation Signal processing algorithms Time domain analysis Frequency estimation Interpolation Fading

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pursuit Controller Performance Guarantees for a Lifeline pursuit-Evasion Game over a Wireless Sensor Network

Pursuit Controller Performance Guarantees for a Lifeline Pur...

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IEEE Conference on Decision and Control

作者： Phoebus Chen Shankar Sastry Department of Electrical Engineering and Computer Sciences University of California Berkeley Berkeley CA USA

ISBN: (纸本)1424401704;9781424401703

pursuit-evasion games have been studied as a generalization of many control problems, and have been also used to study the viability of running control algorithms over sensor networks. We provide a method for computing performance bounds on a sample pursuit-evasion game, the classic lifeline game described by Rufus Isaacs. Given a routing topology and pairwise link probabilities, we compute an n-hop disk model abstraction of a sensor network to model delay and lost packets. Using this model, we then compute a probabilistic barrier that splits the state space of the game into an escape zone and a capture zone. This barrier and the corresponding optimal control laws are the solution to the game. The position of the barrier in the state space provides a sense of how well such a control application can perform over a sensor network

关键词： Wireless sensor networks State-space methods Optimal control Delay Control systems USA Councils pursuit algorithms Routing Network topology Computer networks

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Hierarchical decomposition approach for pursuit-evasion differential game with multiple players

Hierarchical decomposition approach for pursuit-evasion diff...

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IEEE Conference on Aerospace

作者： Jianhua Ge Liang Tang J. Reimann G. Vachtsevanos Impact Technologies LLC Rochester NY USA Department of Electrical and Computer Engineering Georgia Institute of Technology Atlanta GA USA

pursuit-evasion games are among the most widespread, challenging, and important optimization problems. This paper presents a hierarchical decomposition algorithm for pursuit-evasion differential games with multiple pursuers and multiple evaders. The developed algorithm is not only to reduce the complexity of the problem, but also to enable the problem to be solved in a distributed fashion. Consequently, when the scheme is to be implemented, it is possible to increase the speed of the algorithm by breaking it down into multiple independent computational processes

关键词： Game theory Optimal control Paper technology Military computing Vehicle dynamics Energy capture Irrigation pursuit algorithms Biographies Constraint theory

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Adapting Matching pursuit Dictionaries to Waveform Structure using Particle Filtering

Adapting Matching Pursuit Dictionaries to Waveform Structure...

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Sensor Array and Multichannel Signal Processing Workshop

作者： I. Kyriakides A. Papandreou-Suppappola D. Morrell Department of Electrical Engineering Arizona State University Tempe AZ USA Department of Engineering Arizona State University Mesa AZ USA

Although the matching pursuit algorithm can accurately decompose waveforms, its use in real applications is limited. This is because it can be computationally intensive as it is based on selecting elements from complete dictionaries spanning the time-frequency plane of interest. There is, therefore, a need for smaller dictionaries that can still result in accurate waveform decompositions. In this paper, we propose the particle filter matching pursuit algorithm that adapts the dictionary to the waveform structure. This algorithm uses particle filtering, a sequential Monte Carlo approach, to estimate the dictionary suitable for the decomposition of a given waveform, and then uses the matching pursuit algorithm to decompose the waveform. We demonstrate, using simulations, that the particle filtering matching pursuit can decompose waveforms faster than the matching pursuit

关键词： Matching pursuit algorithms Dictionaries Matched filters pursuit algorithms Filtering algorithms Time frequency analysis Data mining Atomic measurements Electronic mail Particle filters

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Controlling Nonlinear Dynamic Systems with Projection pursuit Learning

Controlling Nonlinear Dynamic Systems with Projection Pursui...

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International IEEE Conference on Intelligent Systems, IS

作者： Clodoaldo A. M. Lima Pablo A. D. Castro Andre L. V. Coelho Cynthia Junqueira Fernando J. Von Zuben Laboratory of Bioinformatics and Bio-inspired Computing (LBiC) State University of Campinas-UNICAMP Sao Paulo Brazil Applied Informatics (MIA) University of Fortaleza-UNIFOR Fortaleza Ceara Brazil Laboratory of Signal Processing for Communications (DSPCom) State University of Campinas-UNICAMP Sao Paulo Brazil

Projection pursuit learning (PPL) refers to a well-known constructive learning algorithm characterized by a very efficient and accurate computational procedure oriented to nonparametric regression. It has been employed as a means to counteract some problems related to the design of artificial neural network (ANN) models, namely, the estimation of a (usually large) number of free parameters, the proper definition of the model's dimension, and the choice of the sources of nonlinearities (activation functions). In this work, the potentials of PPL are exploited through a different perspective, namely, in designing one-hidden-layer feedforward ANNs for the adaptive control of nonlinear dynamic systems. For such purpose, the proposed methodology is divided into three stages. In the first, the model identification process is undertaken. In the second, the ANN structure is defined according to an offline control setting. In these two stages, the PPL algorithm estimates not only the optimal number of hidden neurons but also the best activation function for each node. The final stage is performed online and promotes a fine-tuning in the parameters of the identification model and the controller. Simulation results indicate that it is possible to design effective neural models based on PPL for the control of nonlinear multivariate systems, with superior performance when compared to benchmarks

关键词： Nonlinear control systems Control systems Artificial neural networks Aerodynamics Neurons pursuit algorithms Adaptive control Nonlinear dynamical systems Laboratories System identification

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Nonlinear Distance Measure Based Discriminant pursuit Algorithm for Defects Classification in Ultrasonic NDT

Nonlinear Distance Measure Based Discriminant Pursuit Algori...

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World Congress on Intelligent Control and Automation (WCICA)

作者： Xiuli Du Yi Shen Zhiduo Xu Department of Control Science and Engineering Harbin Institute of Technology Harbin Heilongjiang China ChangZhou JianHu Intelligentize Meter Company Limited Changzhou Jiangsu China

Discriminant pursuit selects time-frequency atoms as discriminant features that differentiate signals of different classes. Nonlinear distance measure was proposed to replace the common Euclid distance measure in Fisher's class separability criterion, which was used as discriminant criterion in discriminant pursuit. The presented method emphasizes minimizing the inner distance of the same class mainly. The coefficient vectors obtained by discriminant pursuit represent the time-frequency discriminant features of each class and were feed to the multiplayer perceptron neural network. The results show that the classification based on the proposed method perform best in identifying ultrasonic testing signal with accuracy rate 96-100% and very low mean squared error

关键词： Ultrasonic variables measurement pursuit algorithms Time frequency analysis Atomic measurements Matching pursuit algorithms Dictionaries Acoustic measurements Neural networks Performance evaluation Nondestructive testing

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Analysis of Event Related Potentials using PCA and Matching pursuit on the Time-Frequency Plane

Analysis of Event Related Potentials using PCA and Matching ...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： Selin Aviyente Edward M. Bernat Stephen M. Malone William G. Iacono Department of Electrical and Computer Engineering Michigan State University East Lansing MI USA Department of Psychology University of Minnesota Minneapolis MN USA

Joint time-frequency representations offer a rich representation of event related potentials (ERPs) that cannot be obtained through individual time or frequency domain analysis. This rich representation, however, comes at the expense of increased data volume and the difficulty of interpreting the resulting representations. Therefore, methods that can reduce the large amount of time-frequency data to physiologically meaningful components are essential. The method presented in this paper extends principal component analysis to the time-frequency plane to reduce a large set of ERPs to a small number of significant components. These components are then characterized using a Gabor dictionary to offer a succinct parametrization of the ERP data. The results show that the principal component analysis is successful at extracting components that can be described as the superposition of a small number of Gabor logons, and that the resulting set of logons succinctly represent physiologically meaningful ERP events

关键词： Principal component analysis Matching pursuit algorithms Time frequency analysis Enterprise resource planning Data mining USA Councils Energy resolution Signal resolution pursuit algorithms Cities and towns

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Multichannel Matching pursuit and Applications to Spatial Audio Coding

Multichannel Matching Pursuit and Applications to Spatial Au...

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Asilomar Conference on Signals, Systems & Computers

作者： Michael M. Goodwin Creative Advanced Technology Center Scotts Valley CA USA

Sparse signal modeling has been considered widely in the literature. In this paper, we discuss an extension of the matching pursuit sparse modeling algorithm to the case of simultaneously approximating multiple data signals; we outline the algorithm for general and for sinusoidal dictionaries. We then apply multichannel sinusoidal pursuit (M-SP) to spatial audio coding (SAC). In most SAC schemes, multichannel audio is coded by forming a downmix signal, compressing the down- mix with a legacy coder, and adding side information about spatial properties of the input audio. In the proposed M-SP system, a multichannel model of the input is used to derive the spatial information as well as a parametric model of an appropriate downmix signal. This joint spatial-parametric approach provides a different multichannel audio coding paradigm than that of previously described SAC methods.

关键词： Matching pursuit algorithms Audio coding Dictionaries pursuit algorithms Algorithm design and analysis Brain modeling Parametric statistics Approximation algorithms Frequency Signal analysis

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