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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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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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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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Notes on Data-driven System Approaches

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Acta Automatica Sinica 2009年第6期35卷 668-675页

作者： Jian-Xin XU Zhong-Sheng HOU Department of Electrical and Computer Engineering National University of Singapore Singapore 117576 Singapore Advanced Control Systems Laboratory School of Electronics and Information Engineering Beijing Jiaotong University Beijing 100044 P.R. China

In this paper, we present several considerations centered around the data-driven system approaches. We briefly explore three main issues: the evolving relationship between off-line and on-line data processing methods, the complementary relationship between the data-driven and model-based methods, and the perspectives of data-driven system approaches. Instead of offering solutions to data-driven system problems, which is impossible at the present level of knowledge and research, in this article we aim at categorizing and classifying open problems, exploring possible directions that may offer alternatives or potentials for the four key fields of interests: control, decision making, scheduling, and fault diagnosis.

关键词： Data-driven principal relations problem classification research directions

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Learning Approaches to the Witsenhausen Counterexample From a View of Potential Games

Learning Approaches to the Witsenhausen Counterexample From ...

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

作者： Na Li Jason R.Marden Jeff S.Shamma Department of Control and Dynamical Systems California Institute of Technology Social and Informational Sciences Laboratory California Institute of Technology School of Electrical and Computer Engineering Georgia Institute of Technology

Since Witsenhausen put forward his remarkable counterexample in 1968,there have been many attempts to develop efficient methods for solving this non-convex functional optimization *** there are few methods designed from game theoretic *** this paper,after discretizing the Witsenhausen counterexample and re-writing the formulation in analytical expressions,we use fading memory JSFP with inertia,one learning approach in games,to search for better controllers from a view of potential *** achieve a better solution than the previously known best ***,we show that the learning approaches are simple and automated and they are easy to extend for solving general functional optimization problems.

关键词： Learning Approaches to the Witsenhausen Counterexample From a View of Potential Games

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Gait Recognition Using Wavelet Packet Silhouette Representation and Transductive Support Vector Machines

Gait Recognition Using Wavelet Packet Silhouette Representat...

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Congress on Image and Signal Processing, CISP

作者： Farzin Dadashi Babak N. Araabi Hamid Soltanian-Zadeh Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Hospital Detroit MI USA

Gait is an idiosyncratic biometric that can be used for human identification at a distance and as a result gained growing interest in intelligent visual surveillance. In this paper, an efficient gait recognition method based on describing subject outer body contour deformations using wavelet packets is proposed. With the use of matching pursuit algorithm, k bases of wavelet packet tree that have maximum similarity to the signal are selected and corresponding coefficients are used as features. Finally, transductive support vector machine (TSVM) classification is utilized on computed eigengait space for semi-supervised identification. The proposed method of selecting features which uses a complete orthogonal or near orthogonal basis from a wavelet packet library of bases and investigating the correlational structure of gait features for each individual using TSVM, result in encouraging identification performance.

关键词： Wavelet packets Support vector machines Matching pursuit algorithms Biometrics Humans Machine intelligence Surveillance Pursuit algorithms Support vector machine classification Libraries

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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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H∞ Filtering for Neutral Stochastic systems with Time-Varying Delays

H∞ Filtering for Neutral Stochastic Systems with Time-Varyi...

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

作者： Lin Li Yingmin Jia Junping Du Hideki Kokame 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 College of Engineering Osaka Prefecture University

This paper is devoted to the problem of H filtering for a class of neutral stochastic systems with both discrete and distributed time-varying *** objective is to design a full order filter such that the resulting filtering error system is stochastically asymptotically stable with a prescribed H∞performance *** on the stability theory of stochastic systems,a delay-dependent and rate-dependent sufficient condition for the existence of filter is obtained in terms of linear matrix inequalities（LMIs）.The corresponding filter design method is also proposed,while the explicit expression for the desired filter is given.A numerical example is finally included to illustrate the effectiveness of the proposed method.

关键词： Filtering for Neutral Stochastic systems with Time-Varying Delays filter

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A novel fingerprint recognition algorithm using 2DPCA and RBFNN

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Journal of Information and Computational Science 2009年第4期6卷 1899-1906页

作者： Ni, Jianyun Xu, Qinmin Lei, Ming Luo, Jing Tianjin Key Laboratory for Control Theory and Applications in Complicated Systems Tianjin University of Technology Tianjin 300191 China School of Electrical Engineering Tianjin University of Technology Tianjin 300191 China School of Computer Science and Technology Tianjin University of Technology Tianjin 300191 China College of Electrical Engineering and Automation Tianjin Polytechnic University Tianjin 300160 China

Fingerprint recognition algorithm based on minutiae has large computation, slow recognition speed as a result of complex processing, such as image enhance, smooth, binary, and thinning. A novel fingerprint recognition algorithm Using 2DPCA(Two-Dimensional Principal Component Analysis) has been proposed in this paper. Firstly, original images are decomposed into high-frequency and lowfrequency components with the help of Wavelet Transform (WT), and high-frequency components are ignored, so the prime features of original images can be attained. Secondly, the projected features are solved by 2DPCAFinallyfingerprint recognition can be realized by Radial Basis Function Neural Network (RBFNN). The algorithm combines the optimization of the 2DPCA and the adaptability of RBFNN. The experimental results based on FVC2002 have verified that the proposed algorithm has higher robustness to the fingerprint images which has the change of shift and rotation and light than IDFFWNN. © 2009 Binary Information Press.

关键词： Wavelet transforms

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