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Designs for high performance PAL-based imaging systems

APPLIED OPTICS 2012年第21期51卷 5310-5317页

作者： Hui, Dong Zhang, Mei Geng, Zheng Zhang, Yunfang Duan, Jingyuan Shi, Ancun Hui, Li Fang, Qing Liu, Yuliang Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Chinese Acad Sci Inst Semicond Optoelect Syst Lab Beijing 100083 Peoples R China

In this study, we investigate methods to optimize the design of a panoramic annular lens (PAL) system. The design details of a PAL surveillance system, an anamorphic PAL surveillance system, a phone camera with a PAL attachment, and a PAL endoscope system are described. All these designs are optimized using a standard optical software package (Zemax). The results combine very good image quality with a modulation transfer function above 0.3, which is within the cutoff frequency of sensor chips. (C) 2012 Optical Society of America

关键词： Image processing Image quality Imaging systems Optical design Optical design software Optical standards

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ENVIRONMENT COUPLED METRICS LEARNING FOR UNCONSTRAINED FACE VERIFICATION

ENVIRONMENT COUPLED METRICS LEARNING FOR UNCONSTRAINED FACE ...

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19th IEEE International Conference on Image Processing (ICIP)

作者： Cai, Xinyuan Wang, Chunheng Xiao, Baihua Zhou, Ji Chen, Xue Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

ISBN: (纸本)9781467325332;9781467325349

Making recognition more reliable under unconstrained environment is one of the most important challenges for real-world face recognition. In this paper, we propose a novel approach for unconstrained face verification. First, we use a spectral-clustering method based on Structural Similarity index to estimate the captured environments of facial images. Then for each pair of environments, we learn two coupled metrics, such that facial images captured in different environments can be transformed into a media subspace, and high recognition performance can be achieved. The coupled transformations are jointly determined by solving an optimization problem in the multi-task learning framework. Experimental results on the benchmark dataset (LFW) show the effectiveness of the proposed method in face verification across varying environments.

关键词： Face verification metric learning unconstrained environment multi-task learning

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International Joint Conference on Neural Networks (IJCNN)

作者： Song, Shuangyong Li, Qiudan Zheng, Xiaolong Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100080 Peoples R China

ISBN: (纸本)9781467314909

The rapid increasing popularity of micro-blogging has made it an important information seeking channel. By detecting recent popular topics from micro-blogging, we have opportunities to gain insights into internet hotspots. Generally, a topic's popularity is determined by two primary factors. One is how frequently a topic is discussed by users, and the other is how much influence those users have, since topics shown in the influential users' posts are more likely to attract others' attention. However, existing approaches interpret a topic's popularity with only the number of keywords related to it, which neglect the importance of the user influence to information diffusion in micro-blogging. In this paper, drawing upon the Cognitive Authority Theory and Social Network Theory, we propose a novel model that detects the most popular topics in micro-blogging with a user interest-based method. The proposed model first constructs a topic graph according to users' interests and their following relationship, and then calculates the topics' popularity with a link-based ranking algorithm. The popular topics detected by the method can reflect the relationship among users' interests, and the topics in the posts of influential users can be highlighted. Experimental results on the data of Twitter, a well-known and feature-rich micro-blogging service, show that the proposed method is effective in popular topic discovery.

关键词： Twitter micro-blogging topic ranking user interest social network theory PageRank

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Optimal control of unknown nonaffine nonlinear discrete-time systems based on adaptive dynamic programming

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AUTOMATICA 2012年第8期48卷 1825-1832页

作者： Wang, Ding Liu, Derong Wei, Qinglai Zhao, Dongbin Jin, Ning Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Illinois Dept Elect & Comp Engn Chicago IL 60607 USA

An intelligent-optimal control scheme for unknown nonaffine nonlinear discrete-time systems with discount factor in the cost function is developed in this paper. The iterative adaptive dynamic programming algorithm is introduced to solve the optimal control problem with convergence analysis. Then, the implementation of the iterative algorithm via globalized dual heuristic programming technique is presented by using three neural networks, which will approximate at each iteration the cost function, the control law, and the unknown nonlinear system, respectively. In addition, two simulation examples are provided to verify the effectiveness of the developed optimal control approach. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Adaptive critic designs Adaptive dynamic programming Approximate dynamic programming Globalized dual heuristic programming Intelligent control Neural network Optimal control

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Neural-Network-Based Optimal control for a Class of Unknown Discrete-Time Nonlinear systems Using Globalized Dual Heuristic Programming

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IEEE TRANSACTIONS ON AUTOMATION SCIENCE AND ENGINEERING 2012年第3期9卷 628-634页

作者： Liu, Derong Wang, Ding Zhao, Dongbin Wei, Qinglai Jin, Ning Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Illinois Dept Elect & Comp Engn Chicago IL 60607 USA

In this paper, a neuro-optimal control scheme for a class of unknown discrete-time nonlinear systems with discount factor in the cost function is developed. The iterative adaptive dynamic programming algorithm using globalized dual heuristic programming technique is introduced to obtain the optimal controller with convergence analysis in terms of cost function and control law. In order to carry out the iterative algorithm, a neural network is constructed first to identify the unknown controlled system. Then, based on the learned system model, two other neural networks are employed as parametric structures to facilitate the implementation of the iterative algorithm, which aims at approximating at each iteration the cost function and its derivatives and the control law, respectively. Finally, a simulation example is provided to verify the effectiveness of the proposed optimal control approach.

关键词： Adaptive dynamic programming approximate dynamic programming globalized dual heuristic programming intelligent control neural networks optimal control

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Parallel Traffic management system Helps 16th Asian Games

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IEEE INTELLIGENT systemS 2012年第3期27卷 74-78页

作者： Xiong, Gang Liu, Sheng Dong, Xisong Zhu, Fenghua Hu, Bin Fan, Dong Zhang, Zi Chinese Acad Sci Beijing Engn Res Ctr Intelligent Technol & Syst State Key Lab Management & Control Complex Syst Beijing 100864 Peoples R China Chinese Acad Sci Cloud Comp Ind Technol Innovat & Incubat Ctr Dongguan Res Inst Beijing 100864 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100864 Peoples R China

To overcome public transportation problems during the 16th Asian Games held in Guanhzhou China, a PtMS (Parallel Transportation management system), a novel application of Intelligent Transportation systems, was introduced for effective and convenient traffic management. Results show that PtMS has successfully enhanced public traffic management, raising it from experience-based policy formulation plus manual implementation to scientific computing-based policy generation plus implementation with intelligent systems.

关键词： Parallel Transportation management system Public Transit Asian Games Bus Rapid Transit Bus management Taxi management Artificial Transportation system

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A study on ARMA model based corporate equipment maintenance expenditure prediction

A study on ARMA model based corporate equipment maintenance ...

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2012 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2012

作者： Lv, Minhui Zhao, Hongxia Shchool of Management Department of Equipment Economics and Management Naval University of Engineering Wuhan China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467324007

This paper focuses on macro prediction of corporate equipment maintenance expenditure, adopts ARMA to establish the model for historical data of corporate equipment maintenance expenditure and makes demand analysis and prediction so as to provide a scientific basis for decision makers in equipment maintenance expenditure prediction, and they can control the overall budget for equipment maintenance. Based on analysis and compassion of actual model calculation results, the paper reaches the conclusion that ARMA model enjoys an advantage over traditional predicting models in corporate equipment maintenance prediction. © 2012 IEEE.

关键词： Forecasting

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An Extended Path Following Algorithm for Graph-Matching Problem

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IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE 2012年第7期34卷 1451-1456页

作者： Liu, Zhi-Yong Qiao, Hong Xu, Lei Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing 100190 Peoples R China Chinese Univ Hong Kong Dept Comp Sci & Engn Shatin Hong Kong Peoples R China

The path following algorithm was proposed recently to approximately solve the matching problems on undirected graph models and exhibited a state-of-the-art performance on matching accuracy. In this paper, we extend the path following algorithm to the matching problems on directed graph models by proposing a concave relaxation for the problem. Based on the concave and convex relaxations, a series of objective functions are constructed, and the Frank-Wolfe algorithm is then utilized to minimize them. Several experiments on synthetic and real data witness the validity of the extended path following algorithm.

关键词： Graph matching convex relaxation concave relaxation directed graph PATH following algorithm

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Co-evolution-based mechanism design for sponsored search advertising

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ELECTRONIC COMMERCE RESEARCH AND APPLICATIONS 2012年第6期11卷 537-547页

作者： Yuan, Yong Zeng, Daniel Univ Arizona Dept Management Informat Syst Tucson AZ 85721 USA Chinese Acad Sci State Key Lab Management & Control Complex Syst Inst Automat Beijing Peoples R China Beijing Engn Res Ctr Intelligent Syst & Technol Beijing Peoples R China

Sponsored search advertising (SSA), the primary revenue source of Web search engine companies, has become the dominant form of online advertising. Search engine companies, such as Google and Baidu, are naturally interested in SSA mechanism design with the aim to improve the overall effectiveness and profitability of SSA ecosystems. Due to model intractability, however, traditional game theory and mechanism design frameworks provide only limited help as to the design and evaluation of practical SSA mechanisms. In this paper, we propose a niche-based co-evolutionary simulation approach, aiming at computationally evaluating SSA auction mechanisms based on advertisers' equilibrium bidding behavior generated through co-evolution of their bidding strategies. Using this approach, we evaluate and compare key performance measures of several practical SSA auction mechanisms, including the generalized first and second price auction, the Vickrey-Clarke-Groves mechanism, and a novel hybrid mechanism adopted by ***, a major search engine in China. (C) 2012 Elsevier B.V. All rights reserved.

关键词： Sponsored search advertising Mechanism design Co-evolutionary simulation Niche-based evolution

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Tracking control of a Closed-Chain Five-Bar Robot With Two Degrees of Freedom by Integration of an Approximation-Based Approach and Mechanical Design

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IEEE TRANSACTIONS ON systemS MAN AND CYBERNETICS PART B-CYBERNETICS 2012年第5期42卷 1470-1479页

作者： Cheng, Long Hou, Zeng-Guang Tan, Min Zhang, W. J. Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Saskatchewan Dept Mech Engn Saskatoon SK S7N 5A9 Canada

The trajectory tracking problem of a closed-chain five-bar robot is studied in this paper. Based on an error transformation function and the backstepping technique, an approximation-based tracking algorithm is proposed, which can guarantee the control performance of the robotic system in both the stable and transient phases. In particular, the overshoot, settling time, and final tracking error of the robotic system can be all adjusted by properly setting the parameters in the error transformation function. The radial basis function neural network (RBFNN) is used to compensate the complicated nonlinear terms in the closed-loop dynamics of the robotic system. The approximation error of the RBFNN is only required to be bounded, which simplifies the initial "trail-and-error" configuration of the neural network. Illustrative examples are given to verify the theoretical analysis and illustrate the effectiveness of the proposed algorithm. Finally, it is also shown that the proposed approximation-based controller can be simplified by a smart mechanical design of the closed-chain robot, which demonstrates the promise of the integrated design and control philosophy.

关键词： Adaptive backstepping closed-chain robot design neural network tracking transient performance.

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