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A framework of distributed dynamic multi-radio multi-channel multi-path routing protocol in Wireless Mesh Networks

A framework of distributed dynamic multi-radio multi-channel...

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International Conference on Information Networking

作者： Xiaofei Wang Wei Cai Ye Yan Taekyoung Kwon Yanghee Choi Wenhua Zeng Department of Computer Science and Engineering Seoul National University South Korea Software School Xiamen University China Department of Computing Hong Kong Polytechnic University Hong Kong China

ISBN: (纸本)9781424445264

Wireless mesh networks (WMNs) have gained a lot of attention recently. Many efforts are made to design proper routing protocols for WMNs. Existing multi-radio multi-channel routing protocols utilize only one path for transmission, and some multi-path routing protocols consider only single channel situation, in which multi-path routing won't improve end-to-end throughput efficiently. In our paper, we propose a framework for distributed reactive routing protocol in WMNs, which utilizes multi-radio multi-channel technique, as well as multi-path transmission strategy. Dynamic channel assignment is used to avoid the inter-flow and intra-flow channel competition and interference. Our protocol establishes and maintains two or more channel-dimensional disjoint paths, and then every data flow is splitted into multiple paths, in order to increase the total end-to-end transmission throughput. Demo and NS2 simulations are carried out for the evaluation of the performance of our proposed protocol comparing with AODV and other related routing protocols. It is shown our proposal can increase end-to-end throughput significantly.

关键词： Routing protocols Wireless mesh networks Throughput Interference Switches Proposals computer science computer networks Distributed computing Communication channels

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Frequency-domain approach to robust iterative learning controller design for uncertain time-delay systems

Frequency-domain approach to robust iterative learning contr...

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Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference

作者： Deyuan Meng Yingmin Jia Junping Du Fashan Yu the Department of Systems and Control Beihang University (BUAA) the Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and TechnologyBeijing University of Posts and Telecommunications the School of Electrical Engineering and Automation Henan Polytechnic University

This paper deals with the robust iterative learning control(ILC) for time-delay systems(TDS) with both model and delay *** ILC algorithm with anticipation in time is considered,and a frequency-domain approach to its design is *** shows that a necessary and sufficient convergence condition can be provided in terms of three design parameters:the lead time,the learning gain,and the performance weighting *** particular,if the lead time is chosen as just the delay estimate,then the convergence condition is derived independent of the delay and the *** this case,with the selection of the performance weighting function,the perfect tracking can be achieved,or the least upper bound of the L2-norm of the limit tracking error can be guaranteed less than the least upper bound of the L2-norm of the initial tracking error.

关键词： Iterative learning control time-delay systems frequency-domain approach anticipation in time

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Gene Selection of Multiple Cancer Types via Huberized Multi-class Support Vector Machine

Gene Selection of Multiple Cancer Types via Huberized Multi-...

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Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference

作者： Juntao Li Yingmin Jia Junping Du Fashan Yu the Department of Systems and Control Beihang University (BUAA) the Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and TechnologyBeijing University of Posts and Telecommunications the School of Electrical Engineering and Automation Henan Polytechnic University

This paper proposes a new type of regularization in the context of multi-class support vector machine for simultaneous classification and gene *** combining the huberized hinge loss function and the elastic net penalty,the proposed support vector machine can do automatic gene selection and further encourage a grouping effect in the process of building classifiers,thus leading a sparse multi-classifiers with enhanced ***,a reasonable correlation between the two regularization parameters is proposed and an efficient solution path algorithm is *** of microarray classification are performed on the leukaemia data set to verify the obtained results.

关键词： Gene selection grouping effect microarray classification solution path support vector machine(SVM)

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Elastic block set reconstruction for face recognition

Elastic block set reconstruction for face recognition

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IEEE International Conference on Image Processing

作者： Dong Li Xudong Xie Kin-Man Lam Zhigang Jin Department of Electronic and Information Engineering Hong Kong Polytechnic University Hong Kong China TNLIST and Department of Automation Tsinghua University China School of Computer Science and Technology Tianjin University TJU China

In this paper, a novel face recognition algorithm named elastic block set reconstruction (EBSR) is proposed. In our method, the EBSR face is used to represent a set of training faces and to simulate different factors in a query image. An EBSR face is constructed by using the blocks from the training face images which best match to the blocks of the query image at the corresponding locations. The elastic local reconstruction (ELR) error is then used to evaluate how well a block pair matches, and the query image is classified based on the accumulated reconstruction error. The proposed method can effectively explore local information in the training set and deal with various conditions well. Also, the reconstruction error can be considered as a kind of dissimilarity measure, which gives a new approach to designing the training set so as to maximize robustness of recognition. Experiments show that consistent and promising results are obtained.

关键词： Face recognition Image reconstruction Robustness Lighting Linear discriminant analysis Scattering Voting Testing Management training Automation

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Reports of the AAAI 2009 spring symposia

Reports of the AAAI 2009 spring symposia

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作者： Bao, Jie Bojars, Uldis Choudhury, Tanzeem Ding, Li Greaves, Mark Kapoor, Ashish Louchart, Sandy Mehta, Manish Nebel, Bernhard Nirenburg, Sergei Oates, Tim Roberts, David L. Sanfilippo, Antonio Stojanovic, Nenad Stubbs, Kristen Thomaz, Andrea L. Tsui, Katherine Woelfl, Stefan Tetherless World Constellation Rensselaer Polytechnic Institute United States Social Software Unit of DERI Galway Ireland Computer Science Department Dartmouth College United States Knowledge Systems at Vulcan Inc United States Adaptive Systems and Interaction Group Microsoft Research Redmond United States School for Mathematics and Computer Sciences Heriot-Watt University United Kingdom School ot Interactive Computing Georgia Institute of Technology United States Department of Computer Science University of Freiburg Germany Computer Science and Electrical Engineering Department University of Maryland Baltimore County United States Pacific Northwest National Laboratory Richland WA United States University of Karlsruhe Germany IRobot Corporation United States University of Massachusetts Lowell United States

The Association for the Advancement of Artificial Intelligence, in cooperation with Stanford university's Department of computer science, was pleased to present the 2009 Spring Symposium Series, held Monday through Wednesday, March 23-25, 2009, at Stanford university. The titles of the nine symposia were Agents That Learn from Human Teachers, Benchmarking of Qualitative Spatial and Temporal Reasoning Systems, Experimental Design for Real- World Systems, Human Behavior Modeling, Intelligent Event Processing, Intelligent Narrative Technologies II, Learning by Reading and Learning to Read, Social Semantic Web: Where Web 2.0 Meets Web 3.0, and Technosocial Predictive Analytics. The goal of the Agents That Learn from Human Teachers symposium was to investigate how we can enable software and robotics agents to leam from real-time interaction with an everyday human partner. The aim of the Benchmarking of Qualitative Spatial and Temporal Reasoning Systems symposium was to initiate the development of a problem repository in the field of qualitative spatial and temporal reasoning and identify a graded set of challenges for future midterm and long-term research. The Experimental Design symposium discussed the challenges of evaluating AI systems. The Human Behavior Modeling symposium explored reasoning methods for understanding various aspects of human behavior, especially in the context of designing intelligent systems that interact with humans. The Intelligent Event Processing symposium discussed the need for more Al-based approaches in event pro-cessing and defined a kind of research agenda for the field, coined as intelligent complex event processing (iCEP). The Intelligent Narrative Technologies IIAAAI symposium discussed innovations, progress, and novel techniques in the research domain. The Learning by Reading and Learning to Read symposium explored two aspects of making natural language texts semantically accessible to, and processable by, machines. The Social Semantic

关键词： Benchmarking

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H∞-based design approach to discrete-time learning control systems with iteration-varying disturbances

H∞-based design approach to discrete-time learning control ...

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Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference

This paper is concerned with the iterative learning control(ILC) problem for discrete-time systems with iterationvarying *** the so-called super-vector approach to ILC,the discrete domain bounded real lemma is employed to develop a sufficient condition ensuring both the stability and the desired H∞ performance of the ILC *** is shown that this sufficient condition can be presented in terms of linear matrix inequalities(LMIs),which can also determine the learning gain matrix.A numerical simulation example is included to validate the theoretical results.

关键词： Iterative learning control discrete-time systems iteration-varying disturbances H_∞ performance linear matrix inequality

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An Improved OIF Elman Neural Network Model with Direction Profit Factor and Its Applications

An Improved OIF Elman Neural Network Model with Direction Pr...

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International Conference on Machine Vision (ICMV)

作者： Ming Li Limin Wang Yang Liu Ying Liu Qian Sun Xuming Han Department of Information Changchun Taxation College Changchun China School of Computing and Software Engineering Southern Polytechnic State University USA College of Computer Science and Technology Jilin University Changchun China Institute of Information and Spreading Engineering Changchun University of Technology Changchun China

Output-input feedback (OIF) Elman neural network is a dynamic feedback network. An improved model is proposed based on the OIF Elman neural network by introducing direction profit factor in this paper. Moreover, the proposed model is applied to forecast the composite index of stock. In addition, some comparisons are also made when the stock exchange is performed using prediction results from OIF Elman neural network. Simulation results show that the proposed model is feasible and effective in the finance field. It shows that the proposed model can not only improve the forecasting precision evidently and possess the characteristic of quick convergence but also provide a good reference tool for investors to obtain more profits.

关键词： Neural networks Predictive models Artificial neural networks Stock markets Neurofeedback State feedback Finance Machine vision Application software computer networks

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Distributed H∞ consensus control for networks of multiple agents with linear coupling dynamics

Distributed H∞ consensus control for networks of multiple a...

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SICE Annual Conference

作者： Yang Liu Yingmin Jia Junping Du Fashan Yu Department of Systems and Control Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

This paper is devoted to the consensus control for a network of autonomous agents with high-dimension linear coupling dynamics and subject to external disturbances. By transforming the consensus control problem into an H infin control problem, we propose a distributed state feedback protocol, and obtain conditions in terms of linear matrix inequalities (LMIs) to ensure the consensus with a prescribed H infin performance level for networks with zero and nonzero communication delays, respectively. Furthermore, the undetermined feedback matrix of the proposed protocol is also solved. A numerical example is included to validate the theoretical results.

关键词： Control systems Communication system control Protocols Multiagent systems Vehicle dynamics Automatic control Telecommunication control Electronic mail Linear feedback control systems State feedback

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Adaptive multi-class support vector machine for microarray classification and gene selection

Adaptive multi-class support vector machine for microarray c...

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SICE Annual Conference

作者： Juntao Li Yingmin Jia Junping Du Fashan Yu Department of Systems and Control Beihang University Beijing China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo Henan China

This paper proposes an adaptive multi-class support vector machine for simultaneous microarray classification and gene selection. By evaluating the gene ranking significance, the adaptive multi-class support vector machine is shown to encourage an adaptive grouping effect in the process of building classifiers, thus leading a sparse multi-classifiers with enhanced interpretability. Based on a reasonable correlation between the two regularization parameters, an efficient solution path algorithm is developed for solving the proposed support vector machine. Experiments performed on the leukaemia data set are provided to verify the obtained results.

关键词： Support vector machines Support vector machine classification Electronic mail Programmable control Adaptive control Gene expression Learning systems Automatic control Control systems Telecommunication control

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A New Support Vector Machine for Microarray Classification and Adaptive Gene Selection

A New Support Vector Machine for Microarray Classification a...

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2009 American Control Conference (ACC 2009)

作者： Juntao Li Yingmin Jia Junping Du Fashan Yu Seventh Research Division Beihang University (BUAA) Beijing 100191 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia School of Computer Science and Technology Beijing University of Posts and Telecommunications Beijing 100876 China School of Electrical Engineering and Automation Henan Polytechnic University Jiaozuo 454000 Henan China

ISBN: (纸本)9781424445233

This paper presents a new support vector machine for simultaneous gene selection and microarray classification. By introducing the adaptive elastic net penalty which is a convex combination of weighted 1-norm penalty and weighted 2-norm penalty, the proposed support vector machine can encourage an adaptive grouping effect and reduce the shrinkage bias for the large coefficients. According to a reasonable correlation between the two regularization parameters, the optimal coefficient paths are shown to be piecewise linear and the corresponding solving algorithm is developed. Experiments are performed on leukaemia data that verify the research results.

关键词： Gene selection grouping effect microarray classification solution path support vector machine (SVM) Support Vector Network penalty Self tuning Microarray

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