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World Congress on Intelligent Control and Automation (WCICA)

作者： Xin Cai Shaoyuan Li Ning Li Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai P.R. China Electrical Engineering and Computer Science Queen's University Belfast Belfast UK

As well-known, model predictive control is closely related to optimal control. This paper studies relationships between them and provides a unified framework for optimality analysis of model predictive controllers (MPC). The optimality is evaluated by comparing total performance of MPC with finite and infinite horizon optimal cost. Based on relaxed value iteration method, upper and lower bounds of optimality evaluation functions are expressed explicitly in terms of optimization horizon. These results reveal detailed characteristics on performance of closed-loop MPC systems due to using “receding horizon optimization” implementation style.

关键词： Optimal control Nonlinear systems Cost function Predictive control Predictive models

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Publisher's Note: “Defect-induced bandgap narrowing in low-k dielectrics” [Appl. Phys. Lett. 107, 082903 (2015)]

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Applied Physics Letters 2015年第13期107卷

作者： X. Guo H. Zheng S. W. King V. V. Afanas'ev M. R. Baklanov J.-F. de Marneffe Y. Nishi J. L. Shohet 1Plasma Processing & Technology Laboratory and Department of Electrical and Computer Engineering University of Wisconsin-Madison Madison Wisconsin 53706 USA 2Logic Technology Development Intel Corporation Hillsboro Oregon 97124 USA 3Department of Physics University of Leuven B-3001 Leuven Belgium 4IMEC Kapeldreef 75 B-3001 Leuven Belgium 5Department of Electrical Engineering Stanford University Stanford California 94305 USA

This article was originally published online on 26 August 2015 with the space missing in the name of the sixth author. The name is correct as it appears above.

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Trace Bench: An Open Data Set for Trace-Oriented Monitoring

Trace Bench: An Open Data Set for Trace-Oriented Monitoring

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IEEE International Conference on Cloud Computing Technology and Science (CloudCom)

作者： Jingwen Zhou Zhenbang Chen Ji Wang Zibin Zheng Michael R. Lyu College of Computer National University of Defense Technology Changsha China Science and Technology on Parallel and Distributed Processing Laboratory National University of Defense Technology Changsha China Shenzhen Research Institute The Chinese University of Hong Kong Shenzhen China Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong China

User request trace-oriented monitoring is an effective method to improve the reliability of cloud systems. However, there are some difficulties in getting traces in practice, which hinder the development of trace-oriented monitoring research. In this paper, we release a fine-grained user request-centric open trace data set, called Trace Bench, collected on a real world cloud storage system deployed in a real environment. During collecting, many aspects are considered to simulate different scenarios, including cluster size, request type, workload speed, etc. Besides recording the traces when the monitored system is running normally, we also collect the traces under the situation with faults injected. With a mature injection tool, 14 faults are introduced, including function faults and performance faults. The traces in Trace Bench are clustered in different files, where each file corresponds to a certain scenario. The whole collection work lasted for more than half a year, resulting in more than 360, 000 traces in 361 files. In addition, we also employ several applications based on Trace Bench, which validate the helpfulness of Trace Bench for the field of trace-oriented monitoring.

关键词： Monitoring Servers Educational institutions Instruments Cloud computing Context Fault diagnosis

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Correntropy induced metric based graph regularized non-negative matrix factorization

Correntropy induced metric based graph regularized non-negat...

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International Conference on Security, Pattern Analysis, and Cybernetics (SPAC)

作者： Bin Mao Naiyang Guan Dacheng Tao Xuhui Huang Zhigang Luo College of Science National University of Defense Technology Changsha China College of Computer National University of Defense Technology Science and Technology on Parallel and Distributed Processing Laboratory Changsha China Department of Computer Science and Technology College of Computer National University of Defense Technology Changsha China Faculty of Engineering and Information Technology University of Technology Sydney Sydney NSW Australia

Non-negative matrix factorization (NMF) is an efficient dimension reduction method and plays an important role in many pattern recognition and computer vision tasks. However, conventional NMF methods are not robust since the objective functions are sensitive to outliers and do not consider the geometric structure in datasets. In this paper, we proposed a correntropy graph regularized NMF (CGNMF) to overcome the aforementioned problems. CGNMF maximizes the correntropy between data matrix and its reconstruction to filter out the noises of large magnitudes, and expects the coefficients to preserve the intrinsic geometric structure of data. We also proposed a modified version of our CGNMF which construct the adjacent graph by using sparse representation to enhance its reliability. Experimental results on popular image datasets confirm the effectiveness of CGNMF.

关键词： Robustness Vectors Clustering algorithms Mutual information Measurement computer integrated manufacturing

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A Cloaking-Based Approach to Protect Location Privacy in Location-Based Services

A Cloaking-Based Approach to Protect Location Privacy in Loc...

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第三十三届中国控制会议

作者： Zheng Jiangyu Tan Xiaobin Cliff Zou Niu Yukun Zhu Jin CAS Key Laboratory of Technology in Geo-spatial Information Processing and Application System University of Science and Technology of China Department of Automation University of Science and Technology of China Department of Electrical Engineering and Computer Science University of Central FloridaOrlandoFL 32816-2362

ISBN: (纸本)9781479947249

With the widespread use of mobile devices, the location-based service(LBS) applications become increasingly popular, which introduces the new security challenge to protect user's location privacy. On one hand, a user expects to report his own location as far as possible away from his real location to protect his location privacy. On the other hand, in order to obtain high quality of service(QoS), users are required to report their locations as accurate as possible. To achieve the dedicated tradeoff between privacy requirement and QoS requirement, we propose a novel approach based on cloaking technique. We also discuss the disadvantage of the traditional general system model and propose an improved model. The basic idea of our approach is to select a sub-area from the generated cloaking area as user's reported location. The sub-area may not contain a user's real location,which prevents an adversary from performing attack with side information. Specifically, by defining an objective function with a novel location privacy metric and a QoS metric, we are able to convert the privacy issue to an optimization problem. Then, location privacy metric and QoS metric are given. To reduce the complexity of the optimization, a heuristic algorithm is *** privacy-preserving analysis and comparison with related work [8], we demonstrate the effectiveness and efficiency of our approach.

关键词： Location-based Services,Location Privacy,k-anonymity,Cloaking Area

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Expectation propagation based iterative group wise detection for large-scale multiuser MIMO-OFDM systems

Expectation propagation based iterative group wise detection...

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IEEE Conference on Wireless Communications and Networking

作者： Sheng Wu Linling Kuang Zuyao Ni Jianhua Lu Defeng David Huang Qinghua Guo Shenzhen Key Laboratory of Wireless Broadband Communication and Signal Processing Shenzhen China Department of Electronic Engineering Tsinghua University Beijing China Tsinghua Space Center Tsinghua University Beijing China Research Institute of Information Technology Tsinghua University Beijing China School of Electrical Electronic and Computer Engineering University of Western Australia Australia School of Electrical Computer and Telecommunications Engineering University of Wollongong Australia

For the spatially correlated multiuser MIMO-OFDM channels, the conventional iterative MMSE-SIC detection suffers from a considerable performance loss. In this paper, we use the factor graph framework to design robust detection algorithms by clustering a group of symbols to combat the spatial correlation and using the principle of expectation propagation to improve message passing. Furthermore, as the complexity of detection becomes one of the issues in the design of large-scale multiuser MIMO-OFDM systems, we propose a low-complexity approximate message-passing algorithm by opening the channel transition node, which eliminates the expensive matrix inversions involved in the MMSE-SIC based algorithms. Finally, numerical results are presented to verify the proposed algorithms.

关键词： Complexity theory MIMO Educational institutions Algorithm design and analysis Vectors OFDM Correlation

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Vocal source features for bilingual speaker identification

Vocal source features for bilingual speaker identification

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2013 IEEE China Summit and International Conference on Signal and Information processing, ChinaSIP 2013

作者： Wang, Jianglin Johnson, Michael T. Speech and Signal Processing Laboratory Department of Electrical and Computer Engineering Marquette University Milwaukee United States

ISBN: (纸本)9781479910434

This paper introduces the use of two new features for speaker identification, Residual Phase Cepstrum Coefficients (RPCC) and Glottal Flow Cepstrum Coefficients (GLFCC), to capture speaker-specific characteristics from their vocal excitation patterns. Results on a cross-lingual speaker identification task taken from the NIST 2004 SRE demonstrate that these RPCC and GLFCC features are significantly more accurate than traditional mel-frequency cepstral coefficients (MFCC). In particular, these two new features give better results with smaller amounts of training data, due to lower model complexity. © 2013 IEEE.

关键词： Speech recognition

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On Infinite Time Performance of Nonlinear Model Predictive Controllers

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IFAC Proceedings Volumes 2014年第3期47卷 1916-1921页

作者： Xin Cai Shaoyuan Li Ning Li Kang Li Department of Automation Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Ministry of Education Shanghai 200240 P. R. China School of Electronics Electrical Engineering and Computer Science The Queen's University Belfast Belfast BT7 1NN UK

This paper addresses the problem of infinite time performance of model predictive controllers applied to constrained nonlinear systems. The total performance is compared with a finite horizon optimal cost to reveal performance limits of closed-loop model predictive control systems. Based on the Principle of Optimality, an upper and a lower bound of the ratio between the total performance and the finite horizon optimal cost are obtained explicitly expressed by the optimization horizon. The results also illustrate, from viewpoint of performance, how model predictive controllers approaches to infinite optimal controllers as the optimization horizon increases.

关键词： Model Predictive Control Finite Horizon Optimal Control Value Iteration Principle of Optimality

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Noise-robust modification method for gaussian-based models with application to radar HRRP recognition

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IEEE Geoscience and Remote Sensing Letters 2013年第3期10卷 558-562页

作者： Pan, Mian Du, Lan Wang, Penghui Liu, Hongwei Bao, Zheng National Laboratory of Radar Signal Processing Xidian University Xi'an 710071 China Department of Electrical and Computer Engineering Duke University Durham NC 27708 United States

In this letter, we introduce a novel noise-robust modification method for Gaussian-based models to enhance the performance of radar high-resolution range profile (HRRP) recognition under the test condition of low signal-to-noise ratio (SNR), and we develop an efficient scheme for its computation. This noise-robust modification method is implemented by revising the trained Gaussian-based model according to the estimated SNR of test HRRP. We apply the proposed method to adaptive Gaussian classifier and truncated stick-breaking hidden Markov model. Experimental results demonstrate that the proposed method can significantly improve the average recognition rate for noisy HRRP test samples while offering recognition performance comparable to that of original model for clean HRRP test samples. Moreover, even when the SNR of test HRRP samples is not precisely estimated, we can still obtain an acceptable result with the proposed method. © 2004-2012 IEEE.

关键词： Signal to noise ratio

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Enhancing the Effectiveness of Fungicides by Optimizing Their Combinations

Enhancing the Effectiveness of Fungicides by Optimizing Thei...

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第26届中国控制与决策会议

作者： Xiang Wang Jia Ma Xiaowei Li Xiaodong Zhao Zongli Lin Jie Chen Zhifeng Shao Department of Automation and Key Laboratory of System Control and Information Processing of the Ministry of EducationShanghai Jiao Tong University Department of Resource and Environmental Science School of Agriculture and BiologyShanghai Jiao Tong University School of Biomedical Engineering Shanghai Jiao Tong University Charles L.Brown Department of Electrical and Computer Engineering University of Virginia

In controlling biological diseases, it is often more potent to use a combination of agents than using individual ones. However, the number of possible combinations increases exponentially with the number of agents and their concentrations. It is prohibitive to search for effective agent combinations by trial and error as biological systems are complex and their responses to agents are often a slow process. This motivates to build a suitable model to describe the biological systems and help reduce the number of experiments. In this paper, we consider the use of fungicides to inhibit Bipolarismaydis and construct models that describe the responses to fungicide combinations. Three data-driven modeling methods, the polynomial regression, the artificial neural network and the support vector regression, are compared based on the experimental data of the inhibition rates of the southern corn leaf blight with different fungicide combinations. The analysis of the results demonstrates that the support vector regression is best suited to the construction of the response model in terms of achieving better prediction with fewer experiments.

关键词： agent combinations,complex system,data-driven model,polynomial regression,artificial neural network,support vector regression

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