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International Joint Conference on Neural Networks (IJCNN)

作者： Furao Shen Hui Yu Wataru Kasai Osamu Hasegawa State Key Laboratory for Novel Software Technology Jiangyin Information Technology Research Institute Nanjing University Nanjing China Department of Computer Intelligence and Systems Science Tokyo Institute of Technology Yokohama Japan Imaging Science and Engineering Laboratory Tokyo Institute of Technology Yokohama Japan

An associative memory (AM) system is proposed to realize incremental learning and temporal sequence learning. The proposed system is constructed with three layer networks: The input layer inputs key vectors, response vectors, and the associative relation between vectors. The memory layer stores input vectors incrementally to corresponding classes. The associative layer builds associative relations between classes. The proposed method can incrementally learn key vectors and response vectors; store and recall both static information and temporal sequence information; and recall information from incomplete or noise-polluted inputs. Experiments using binary data, real-value data, and temporal sequences show that the proposed method works well.

关键词： Associative memory Training Context Indexes Prototypes Humans Topology

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software Language engineering: Preface

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2010年 5969 LNCS卷 V-VI页

作者： Van Den Brand, Mark Gaševíc, Dragan Gray, Jeff Dept. of Mathematics and Computer Science Software Engineering and Technology Eindhoven University of Technology Den Dolech 2 5612 AZ Eindhoven Netherlands School of Computing and Information Systems Athabasca University 1 University Drive Athabasca AB T9S 3A3 Canada Department of Computer Science University of Alabama P.O. Box 870290 Tuscaloosa AL United States

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Delay-dependent conditions for monotonic convergence of uncertain ILC systems: An LMI approach

Delay-dependent conditions for monotonic convergence of unce...

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IEEE Conference on Decision and Control

作者： Deyuan Meng Yingmin Jia Junping Du Fashan Yu Seventh Research Division the 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

ISBN: (纸本)9781424477456

This paper deals with the iterative learning control (ILC) problem for uncertain time-delay systems (TDS). In order to ensure monotonic convergence of the ILC process, a sufficient condition is developed using an H ∞ -based framework. It shows that under this framework, the convergence condition is enabled to be delay-dependent and have a formulation in terms of linear matrix inequalities (LMIs). Moreover, formulas for the updating law design can be derived by directly solving LMIs. A numerical example is provided to verify that the delay-dependent condition in LMI forms is effective in producing monotonically convergent ILC algorithms.

关键词： Convergence Symmetric matrices Robustness Delay Uncertainty Performance analysis Linear matrix inequalities

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Quantum State Reduction for Universal Measurement Based Computation

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Physical Review Letters 2010年第2期105卷 020502-020502页

作者： Xie Chen Runyao Duan Zhengfeng Ji Bei Zeng Department of Physics Massachusetts Institute of Technology Cambridge Massachusetts USA Centre for Quantum Computation and Intelligent Systems (QCIS) Faculty of Engineering and Information Technology University of Technology Sydney NSW Australia Department of Computer Science and Technology Tsinghua National Laboratory for Information Science and Technology Tsinghua University Beijing China Perimeter Institute for Theoretical Physics Waterloo Ontario Canada State Key Laboratory of Computer Science Institute of Software Chinese Academy of Sciences Beijing China Institute for Quantum Computing University of Waterloo Waterloo Ontario Canada Department of Combinatorics and Optimization University of Waterloo Waterloo Ontario Canada

Measurement based quantum computation, which requires only single particle measurements on a universal resource state to achieve the full power of quantum computing, has been recognized as one of the most promising models for the physical realization of quantum computers. Despite considerable progress in the past decade, it remains a great challenge to search for new universal resource states with naturally occurring Hamiltonians and to better understand the entanglement structure of these kinds of states. Here we show that most of the resource states currently known can be reduced to the cluster state, the first known universal resource state, via adaptive local measurements at a constant cost. This new quantum state reduction scheme provides simpler proofs of universality of resource states and opens up plenty of space to the search of new resource states.

关键词： Quantum computers

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Observer-Based L_(2)-L_(infinity) Control for a Class of Stochastic systems with Time-Varying Delay

Observer-Based L_(2)-L_(infinity) Control for a Class of Sto...

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2010 49th IEEE Conference on Decision and Control

作者： Lin Li Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control 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)9781424477456

This paper is devoted to the problem of L_(2)-L_(infinity) control for a class of stochastic time-delay systems via observer-based feedback control. The considered observer contains no time-delay. The purpose is to design an observer-based feedback stabilizing controller such that the augmented closed-loop system is stochastically asymptotically stable with a prescribed L_(2)-L_(infinity) performance satisfied. Based on the stochastic stability theory, a delay-dependent sufficient condition is derived in terms of linear matrix inequalities (LMIs). The observer and controller design method is proposed, while the corresponding explicit expression for the observer and controller gain matrices is also given. Finally, numerical examples and simulation results are included to illustrate the effectiveness of the proposed results.

关键词： stochastic systems system clock time varying stability theory Stochastic delay systems controller gain Closed loop systems

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Analysis of Two Robust Learning Control Schemes in the Presence of Random Iteration-Varying Noise

Analysis of Two Robust Learning Control Schemes in the Prese...

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American Control Conference

作者： Deyuan Meng Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control 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)9781424474264

This paper deals with the design problem of robust iterative learning control (ILC), in the presence of noise that is varying randomly from iteration to iteration. Two ILC schemes are considered: one adopts the previous iteration tracking error (PITE) and the other adopts the current iteration tracking error (CITE), in the updating law. For both schemes, the convergence results are obtained by using a frequency-domain approach, and a comparison between them is presented from the viewpoints of the convergence condition, robustness against plant uncertainty, and delay compensation. It shows that sufficient conditions can be derived to bound the tracking error and make its expectation monotonically convergent in the sense of L_(2)-norm, which work effectively with robustness for all admissible plant uncertainties. Furthermore, the sufficient conditions for both schemes can also be formulated in terms of two complementary functions, which do not depend on the delay time as well as the plant uncertainty and, thus, make them convenient to be checked and solved using the frequency-domain tools. Numerical simulations are included to illustrate the effectiveness of the two proposed ILC schemes.

关键词： Iterative learning control monotonic convergence previous iteration tracking error current iteration tracking error random iteration-varying noise delay compensation delay compensation monotone convergence iterative methods Iterative learning control follow error Scheme design problems Delay time Sufficient conditions learning control

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Model Matching Control for MIMO systems with Multiple Time Delays and Its Applications in Adaptive Scheme

Model Matching Control for MIMO Systems with Multiple Time D...

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American Control Conference

作者： Haixia Su Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control 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)9781424474264

This paper considers the model matching problem of multiple-input multiple-output (MIMO) systems with multiple time delays. The reference model is chosen to be the diagonal delay transfer function matrix. A controller is designed for nominal systems. Furthermore, an adaptive control scheme is proposed for uncertain systems with parameter variation. The resulting scheme can guarantee the global stability of the closed-loop systems and the convergence of the tracking errors. A simulation example is included to illustrate the proposed scheme.

关键词： Control system synthesis MIMO Delay effects Programmable control Adaptive control Transfer functions Control systems Uncertain systems Stability Convergence

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A New Resampling Algorithm for Generic Particle Filters

A New Resampling Algorithm for Generic Particle Filters

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American Control Conference

作者： X. Fu Y. Jia J. Du F. Yu Seventh Research Division and the Department of Systems and Control 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)9781424474264

This paper is devoted to the resampling problem of particle filters. We firstly demonstrate the performance of classical Resampling algorithm (also called as systematic resampling algorithm) using a novel metaphor, through which the existing defects of Resampling algorithm is vividly reflected simultaneously. In order to avoid these defects, the exquisite resampling (ER) algorithm is induced which involves some exquisite actions such as comparing the weights by stages and generating the new particles based on quasi-Monte Carlo method. Simulations indicate that the proposed ER algorithm can reduce the sample impoverishment effectively and improve the accuracy of estimation evidently, which confirm that ER algorithm is a competitive alternative to Resampling algorithm.

关键词： resampling algorithm Particle filters

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Non-Fragile Control for Trajectory Tracking of Nonholonomic Mobile Robots

Non-Fragile Control for Trajectory Tracking of Nonholonomic ...

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American Control Conference

作者： Na Ni Yingmin Jia Junping Du Fashan Yu Seventh Research Division and the Department of Systems and Control 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)9781424474264

This paper is devoted to the non-fragile controller design for the trajectory tracking of nonholonomic mobile robots. Using non-linear state feedback and proper coordinate transformation, the model of nonholonomic mobile robots is exactly linearized. Based on which, the non-fragile controller is designed by employing the linear matrix inequality (LMI) approach. Simulation examples are included to illustrate the effectiveness of the proposed controller.

关键词： Trajectory Mobile robots Control systems Tracking Robot kinematics Orbital robotics State feedback Error correction Sliding mode control Laboratories

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L_(2)-L_(infinity) Filter Design for Neutral Stochastic Time-Delay systems

L_(2)-L_(infinity) Filter Design for Neutral Stochastic Time...

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2010 49th IEEE Conference on Decision and Control

ISBN: (纸本)9781424477456

This paper is concerned with the problem of L_(2)-L_(infinity) filtering for a class of neutral stochastic systems with both discrete and distributed time-varying delays. The purpose is focusd on the design of a full order filter such that the resulting filtering error system is stochastically asymptotically stable in the mean square with a prescribed L_(2)-L_(infinity) disturbance attenuation level satisfied. By employing Lyapunov functional and stochastic stability theory, a delay-dependent sufficient condition for the existence of such a filter is obtained in terms of linear matrix inequalities (LMIs). The desired filter can be obtained by solving two LMIs.

关键词： Stochastic delay systems Filters mean square filter design stochastic systems error system stability theory Delay systems Filtration

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