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$H_\infty$ Synchronization for Uncertain Time-Delay Chaotic Systems With One-Sided Lipschitz Nonlinearity

IEEE Access 2018年 6卷 19798-19806页

作者： Zhanshan Zhao Fei Lv Jing Zhang Yanan Du School of Computer Science and Software Engineering Tianjin Polytechnic University Tianjin China State-Owned Assets Administration Tianjin Vocational Institute Tianjin China School of Textiles Tianjin Polytechnic University Tianjin China

This paper addresses H ∞ synchronization for uncertain chaotic systems with one-sided Lipschitz nonlinearity under the output and intrinsic state delays. By utilizing the one-sided Lipschitz condition and quadratic inner boundedness, constructing an appropriate Lyapunov-Krasovskii (LKF), robust controller design conditions based on Lyapunov stability theory are derived for synchronization of chaotic systems under disturbances or perturbations bounded by L 2 norm. By introducing the delay-derivative limits and delay-interval bounds into LKF, the intrinsic state time-varying delay can be tackled by the delayrange-dependent strategy. Less conservative stability condition can be obtained by the further improved inequality of Jensen inequality and reciprocally convex approach, which can lead to the tighter upper bound for integral inequality. Numerical simulations are provided to verify the validity of the proposed methodology for synchronization of chaotic systems.

关键词： Synchronization Chaotic communication Robustness Delays Adaptive control Time-varying systems

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Frontiers of computer science 2017年第2期11卷 307-319页

作者： Chuitian RONG Yasin N. SILVA Chunqing LI School of Computer Science & Software Engineering Tianjin Polytechnic University Tianjin 300387 China School of Mathematical & Natural Sciences Arizona State University Tempe AZ 85281 USA

String similarity join is an essential operation of many applications that need to find all similar string pairs from two given collections. A quantitative way to determine whether two strings are similar is to compute their similarity based on a certain similarity function. The string pairs with similarity above a certain threshold are regarded as results. The current approach to solving the similarity join problem is to use a unique threshold value. There are, however, several scenarios that require the support of multiple thresholds, for instance, when the dataset includes strings of various lengths. In this scenario, longer string pairs typically tolerate much more typos than shorter ones. Therefore, we proposed a so- lution for string similarity joins that supports different simi- larity thresholds in a single operator. In order to support dif- ferent thresholds, we devised two novel indexing techniques： partition based indexing and similarity aware indexing. To utilize the new indices and improve the join performance, we proposed new filtering methods and index probing tech- niques. To the best of our knowledge, this is the first work that addresses this problem. Experimental results on real-world datasets show that our solution performs efficiently while pro- viding a more flexible threshold specification.

关键词： similarity join similarity aware index similarity thresholds

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Using deep learning neural network for block partitioning in H.265/HEVC 11

Using deep learning neural network for block partitioning in...

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11th EAI International Conference on Mobile Multimedia Communications, MOBIMEDIA 2018

作者： Yang, Ming Xie, Ying Yu, Jian Wang, Zhe Wu, Tao College of Computing and Software Engineering Kennesaw State University MariettaGA30060 United States School of Computer Science and Technology Tianjin University Tianjin300072 China College of Science Tianjin University of Technology Tianjin300384 China

ISBN: (纸本)9781631901645

dividing video frames into Coding Tree Units (CTUs) and Coding Units (CUs) is a critical task of video compression in H.265/HEVC video coding standard. In this paper, we utilize deep learning techniques, especially the deep Convolutional Neural Network (CNN) to speed up the block partitioning process. Deep CNNs have achieved break-through improvements on image recognition tasks such as image classifications, object identifications, and image annotations. However, very few work has been done in applying deep CNN to video encoding. Block partitioning in video coding is highly dependent on the content of the video frames, and thus it is naturalto take advantage of the significant capabilities of deep CNN on image content detection and recognition to perform block partitioning and avoid the time-consuming iterative Rate-Distortion-Optimization (RDO) process. Experimental results have shown that the proposed methodology has largely speed up the coding process and has also achieved coding efficiency comparable to the reference software of H.265/HEVC. © 2018 ACM.

关键词： Image coding

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Surface Reconstruction from Normals: A Robust DGP-based Discontinuity Preservation Approach

Surface Reconstruction from Normals: A Robust DGP-based Disc...

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IEEE/CVF Conference on computer Vision and Pattern Recognition

作者： Wuyuan Xie Miaohui Wang Mingqiang Wei Jianmin Jiang Jing Qin College of Computer and Software Engineering Shenzhen University (SZU) Guangdong Key Laboratory of Intelligent Information Processing College of Information Engineering School of Computer Science and Technology Nanjing University of Aeronautics and Astronautics School of Nursing Hong Kong Polytechnic University

ISBN: (纸本)9781728132945

In 3D surface reconstruction from normals, discontinuity preservation is an important but challenging task. However, existing studies fail to address the discontinuous normal maps by enforcing the surface integrability in the continuous domain. This paper introduces a robust approach to preserve the surface discontinuity in the discrete geometry way. Firstly, we design two representative normal incompatibility features and propose an efficient discontinuity detection scheme to determine the splitting pattern for a discrete mesh. Secondly, we model the discontinuity preservation problem as a light-weight energy optimization framework by jointly considering the discontinuity detection and the overall reconstruction error. Lastly, we further shrink the feasible solution space to reduce the complexity based on the prior knowledge. Experiments show that the proposed method achieves the best performance on an extensive 3D dataset compared with the state-of-the-arts in terms of mean angular error and computational complexity.

关键词： Surface reconstruction discontinuities angular misalignment Solution space CONSERVATION optimum performance Arts complexity classes

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Global Exponential Synchronization of Nonlinearly Coupled Reaction-Diffusion Neural Networks 29

Global Exponential Synchronization of Nonlinearly Coupled Re...

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第29届中国控制与决策会议

作者： Yan-Li Huang Bei-Bei Xu Shun-Yan Ren Jin-Liang Wang Wei-Zhong Chen School of Computer Science and Software Engineering Tianjin Polytechnic University School of Mechanical Engineering Tianjin Polytechnic University

ISBN: (纸本)9781509046584

This paper investigates the synchronization problem of nonlinearly coupled reaction-diffusion neural networks(NCRDNNs).By utilizing Lyapunov functional combined with several inequality techniques,a criterion for synchronization of NCRDNNs is *** designed pinning scheme,the synchronization problem of NCRDNNs is further discussed and a sufficient condition for pinning synchronization is also ***,two numerical examples are given to verify the correctness and effectiveness of the theoretical results.

关键词： Exponential Synchronization Coupled Neural Networks Reaction-Diffusion Terms Nonlinear Coupling Pinning Control

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Finite-time Synchronization of Coupled Cohen-Grossberg Neural Networks with Time-varying Delays 36

Finite-time Synchronization of Coupled Cohen-Grossberg Neura...

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第36届中国控制会议

作者： Shui-Han Qiu Yan-Li Huang Jin-Liang Wang Shun-Yan Ren Dong-Fang Liu School of Computer Science and Software Engineering Tianjin Polytechnic University School of Mechanical Engineering Tianjin Polytechnic University

ISBN: (纸本)9781538629185

This paper is concerned with flnite-time synchronization for two models of coupled Cohen-Grossberg neural networks with time-varying *** the first one,linearly coupled Cohen-Grossberg neural networks is *** the second one,nonlinearly coupled Cohen-Grossberg neural networks is *** on flnite-time stability theory,some inequality techniques,and designed controllers,some criteria which make the coupled Cohen-Grossberg neural networks with linear coupling and nonlinear coupling realize synchronization are derived ***,the settling times of synchronization are also ***,a numerical example is given to confirm the effectiveness of the proposed results.

关键词： Finite-time synchronization Coupled Cohen-Grossberg neural networks Nonlinear coupling Linear coupling Time-varying delays

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Passivity Analysis of Multi-Weighted Complex Dynamical Networks with Fixed and Switching Topologies 36

Passivity Analysis of Multi-Weighted Complex Dynamical Netwo...

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第36届中国控制会议

作者： ZHANG Xiao-Xiao WANG Jin-Liang HUANG Yan-Li REN Shun-Yan School of Computer Science and Software Engineering Tianjin Polytechnic University School of Mechanical Engineering Tianjin Polytechnic University

ISBN: (纸本)9781538629185

In this paper,we respectively discuss passivity of multi-weighted complex dynamical networks with fixed and switching ***,several passivity criteria for the complex dynamical network with fixed topology and multi-weights are established by employing Lyapunov functional approach and inequality ***,similar methods are used to derive some sufficient conditions for passivity of multi-weighted complex dynamical networks with switching ***,a numerical example with simulation results is given to show the correctness of the obtained passivity criteria.

关键词： Complex Dynamical Networks Multi-Weights Passivity Fixed Topology Switching Topology

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Towards universal languages for tractable ontology mediated query answering

arXiv

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arXiv 2019年

作者： Zhang, Heng Zhang, Yan You, Jia-Huai Feng, Zhiyong Jiang, Guifei College of Intelligence and Computing Tianjin University Tianjin China School of Computing Engineering and Mathematics Western Sydney University Penrith Australia School of Computer Science and Technology Huazhong University of Technology and Science Wuhan China Department of Computing Science University of Alberta Edmonton Canada College of Software Nankai University Tianjin China

An ontology language for ontology mediated query answering (OMQA-language) is universal for a family of OMQA-languages if it is the most expressive one among this family. In this paper, we focus on three families of tractable OMQA-languages, including first-order rewritable languages and languages whose data complexity of the query answering is in AC0 or PTIME. On the negative side, we prove that there is, in general, no universal language for each of these families of languages. On the positive side, we propose a novel property, the locality, to approximate the first-order rewritability, and show that there exists a language of disjunctive embedded dependencies that is universal for the family of OMQA-languages with locality. All of these results apply to OMQA with query languages such as conjunctive queries, unions of conjunctive queries and acyclic conjunctive queries. Copyright © 2019, The Authors. All rights reserved.

关键词： Ontology

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Impacts of prior parameter distributions on Bayesian evaluation of groundwater model complexity

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Water science and engineering 2018年第2期11卷 89-100页

作者： Saeideh Samani Ming Ye Fan Zhang Yong-zhen Pei Guo-ping Tang Ahmed Elshall Asghar A.Moghaddam Department of Earth Sciences University of Tabriz Department of Scientific Computing Florida State University School of Computer Science and Software Engineering Tianjin Polytechnic University Department of Earth Ocean and Atmospheric Science Florida State University Key Laboratory of Tibetan Environment Changes and Land Surface Processes Institute of Tibetan Plateau Research Chinese Academy of Sciences Environmental Sciences Division Oak Ridge National Laboratory

This study used the marginal likelihood and Bayesian posterior model probability for evaluation of model complexity in order to avoid using over-complex models for numerical simulations. It focused on investigation of the impacts of prior parameter distributions(involved in calculating the marginal likelihood) on the evaluation of model complexity. We argue that prior parameter distributions should define the parameter space in which numerical simulations are made. New perspectives on the prior parameter distribution and posterior model probability were demonstrated in an example of groundwater solute transport modeling with four models, each simulating four column experiments. The models had different levels of complexity in terms of their model structures and numbers of calibrated parameters. The posterior model probability was evaluated for four cases with different prior parameter distributions. While the distributions substantially impacted model ranking, the model ranking in each case was reasonable for the specific circumstances in which numerical simulations were made. For evaluation of model complexity, it is thus necessary to determine the parameter spaces for modeling, which can be done by conducting numerical simulation and usineg engineering judgment based on understanding of the system being studied.

关键词： Marginal likelihood Posterior model probability Advection-dispersion equation Mobile-immobile model Groundwater model

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Passivity and Robust Passivity of Reaction-Diffusion Cohen-Grossberg Neural Networks with Multiple Time-Varying Delays 29

Passivity and Robust Passivity of Reaction-Diffusion Cohen-G...

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第29届中国控制与决策会议

作者： Wei-Zhong CHEN Yan-Li HUANG Jin-Liang WANG Shun-Yan REN School of Computer Science and Software Engineering Tianjin Polytechnic University School of Mechanical Engineering Tianjin Polytechnic University

ISBN: (纸本)9781509046584

The problem of passivity is discussed in this paper for reaction-diffusion Cohen-Grossberg neural networks(CGNNs) with multiple time-varying *** constructing suitable lyapunov functionals and employing some inequality techniques,several sufficient conditions guaranteeing the passivity of CGNNs are ***,several criteria for robust passivity are also derived for the case that parameter uncertainties appear in ***,a numerical example is given to validate the reasonableness and effectiveness of the proposed results.

关键词： Reaction-Diffusion Cohen-Grossberg Neural Networks Passivity Robust Passivity Multiple Time-Varying Delays

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