The Experts below are selected from a list of 255 Experts worldwide ranked by ideXlab platform
Wei Xing Zheng - One of the best experts on this subject based on the ideXlab platform.
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Multiple Lyapunov Functions Analysis Approach for Discrete-Time-Switched Piecewise-Affine Systems Under Dwell-Time Constraints
IEEE Transactions on Automatic Control, 2020Co-Authors: Wei Xing ZhengAbstract:In this technical note, the asymptotic stability analysis and state-feedback control design are investigated for a class of discrete-time switched nonlinear systems via the smooth approximation technique. The modal dwell-time switching property is considered to constrain switchings between nonlinear subsystems. A kind of autonomous switchings, i.e., state-Partition-dependent switching, is introduced within each approximated piecewise-affine (PWA) subsystem. Combining with the state Partition Information, the novel asymptotic stability conditions with less conservatism are derived for the induced switched PWA systems with dual switching mechanism based on the approach of multiple Lyapunov functions in piecewise quadratic form. Then, the design of PWA state-feedback controllers is implemented. The effectiveness of the obtained theoretical results is demonstrated by a numerical example.
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Observer-Based Control for Piecewise-Affine Systems With Both Input and Output Quantization
IEEE Transactions on Automatic Control, 2017Co-Authors: Lixian Zhang, Zepeng Ning, Wei Xing ZhengAbstract:This technical note is concerned with the problem of simultaneous design of observers and controllers for a class of piecewise-affine systems against signal quantization occurring in both measurement output and control input channels. The general scenario is considered that system state and estimated state may not be in the same operating region. By a novel quantization-errordependent Lyapunov function, the stability and H∞ performance criteria are first established for the augmented system composed of a closed-loop control system and an estimation error system with the aid of S-procedure involving the region Partition Information of the original system. Then, by the cone complementary linearization algorithm, the desired observer and controller gains are solved simultaneously such that the resulting closed-loop system is asymptotically stable with a prescribed H∞ performance index. Finally, a networked single-link robot arm is utilized to demonstrate the effectiveness of the proposed control strategy.
Xiaoyi He - One of the best experts on this subject based on the ideXlab platform.
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ICIP - Enhancing HEVC Compressed Videos with a Partition-Masked Convolutional Neural Network
2018 25th IEEE International Conference on Image Processing (ICIP), 2018Co-Authors: Xiaoyi He, Qiang Hu, Xiaoyun Zhang, Chongyang ZhangAbstract:In this paper, we propose a Partition-masked Convolution Neural Network (CNN) to achieve compressed-video enhancement for the state-of-the-art coding standard, High Efficiency Video Coding (HECV). More precisely, our method utilizes the Partition Information produced by the encoder to guide the quality enhancement process. In contrast to existing CNN-based approaches, which only take the decoded frame as the input to the CNN, the proposed approach considers the coding unit (CU) size Information and combines it with the distorted decoded frame such that the degradation introduced by HEVC is reduced more efficiently. Experimental results show that our approach leads to over 9.76% BD-rate saving on benchmark sequences, which achieves the state-of-the-art performance.
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Enhancing HEVC Compressed Videos with a Partition-Masked Convolutional Neural Network
2018 25th IEEE International Conference on Image Processing (ICIP), 2018Co-Authors: Xiaoyi He, Qiang Hu, Xiaoyun Zhang, Chongyang ZhangAbstract:In this paper, we propose a Partition-masked Convolution Neural Network (CNN) to achieve compressed-video enhancement for the state-of-the-art coding standard, High Efficiency Video Coding (HECV). More precisely, our method utilizes the Partition Information produced by the encoder to guide the quality enhancement process. In contrast to existing CNN-based approaches, which only take the decoded frame as the input to the CNN, the proposed approach considers the coding unit (CU) size Information and combines it with the distorted decoded frame such that the degradation introduced by HEVC is reduced more efficiently. Experimental results show that our approach leads to over 9.76% BD-rate saving on benchmark sequences, which achieves the state-of-the-art performance.
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Partition-Aware Adaptive Switching Neural Networks for Post-Processing in HEVC
IEEE Transactions on Multimedia, 1Co-Authors: Xiaoyi He, Hongkai Xiong, Feng WuAbstract:This paper addresses neural network based post-processing for the state-of-the-art video coding standard, High Efficiency Video Coding (HEVC). We first propose a Partition-aware Convolution Neural Network (CNN) that utilizes the Partition Information produced by the encoder to assist in the postprocessing. In contrast to existing CNN-based approaches, which only take the decoded frame as input, the proposed approach considers the coding unit (CU) size Information and combines it with the distorted decoded frame such that the artifacts introduced by HEVC are efficiently reduced. We further introduce an adaptive switching network (ASN) that consists of multiple independent CNNs to adaptively handle the variations in content and distortion within compressed-video frames, providing further reduction in visual artifacts. Additionally, an iterative training procedure is proposed to train these independent CNNs attentively on different local patch-wise classes. Experiments on benchmark sequences demonstrate the effectiveness of our Partition-aware and adaptive-switching networks.
Zheng Zheng - One of the best experts on this subject based on the ideXlab platform.
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Using Partition Information to Prioritize Test Cases for Fault Localization
2015 IEEE 39th Annual Computer Software and Applications Conference, 2015Co-Authors: Xiao-yi Zhang, Dave Towey, Tsong Yueh Chen, Zheng ZhengAbstract:Fault Localization Prioritization (FLP) aims at reordering existing test cases so that the location of detected faulty components can be identified earlier, using certain fault localization techniques. Although some researchers have proposed adaptive prioritization strategies with white-box code coverage Information, such Information may not always be available. In this paper, we address the FLP problem using black-box Information derived from Partitioning the input domain. Based on the well-known technique of Spectra-Based Fault Localization (SBFL), three test case prioritization strategies are designed following some basic SBFL heuristics. The implementation of these proposed strategies relies only on the Partition Information, and does not require any test case execution history. Experiments show that our strategies, when compared with pure random selection, result in a faster localization of faulty statements, reducing the number of test case executions required. Here, we analyze the characteristics and merits of the three proposed strategies.
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COMPSAC - Using Partition Information to Prioritize Test Cases for Fault Localization
2015 IEEE 39th Annual Computer Software and Applications Conference, 2015Co-Authors: Xiao-yi Zhang, Dave Towey, Tsong Yueh Chen, Zheng ZhengAbstract:Fault Localization Prioritization (FLP) aims at reordering existing test cases so that the location of detected faulty components can be identified earlier, using certain fault localization techniques. Although some researchers have proposed adaptive prioritization strategies with white-box code coverage Information, such Information may not always be available. In this paper, we address the FLP problem using black-box Information derived from Partitioning the input domain. Based on the well-known technique of Spectra-Based Fault Localization (SBFL), three test case prioritization strategies are designed following some basic SBFL heuristics. The implementation of these proposed strategies relies only on the Partition Information, and does not require any test case execution history. Experiments show that our strategies, when compared with pure random selection, result in a faster localization of faulty statements, reducing the number of test case executions required. Here, we analyze the characteristics and merits of the three proposed strategies.
Tarek Abdelzaher - One of the best experts on this subject based on the ideXlab platform.
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Schedulability bound for integrated modular avionics Partitions
2015 Design Automation & Test in Europe Conference & Exhibition (DATE), 2015Co-Authors: Tarek AbdelzaherAbstract:In the avionics industry, as a hierarchical scheduling architecture Integrated Modular Avionics System has been widely adopted for its isolating capability. In practice, in an early development phase, a system developer does not know much about task execution times, but only task periods and IMA Partition Information. In such a case the schedulability bound for a task in a given Partition tells a developer how much of the execution time the task can have to be schedulable. Once the developer knows the bound, then the developer can deal with any combination of execution times under the bound, which is safe in terms of schedulability. We formulate the problem as linear programming that is commonly used in the avionics industry for schedulability analysis, and compare the bound with other existing ones which are obtained with no period Information.
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DATE - Schedulability bound for integrated modular avionics Partitions
Design Automation & Test in Europe Conference & Exhibition (DATE) 2015, 2015Co-Authors: Tarek AbdelzaherAbstract:In the avionics industry, as a hierarchical scheduling architecture Integrated Modular Avionics System has been widely adopted for its isolating capability. In practice, in an early development phase, a system developer does not know much about task execution times, but only task periods and IMA Partition Information. In such a case the schedulability bound for a task in a given Partition tells a developer how much of the execution time the task can have to be schedulable. Once the developer knows the bound, then the developer can deal with any combination of execution times under the bound, which is safe in terms of schedulability. We formulate the problem as linear programming that is commonly used in the avionics industry for schedulability analysis, and compare the bound with other existing ones which are obtained with no period Information.
Lixian Zhang - One of the best experts on this subject based on the ideXlab platform.
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Observer-Based Control for Piecewise-Affine Systems With Both Input and Output Quantization
IEEE Transactions on Automatic Control, 2017Co-Authors: Lixian Zhang, Zepeng Ning, Wei Xing ZhengAbstract:This technical note is concerned with the problem of simultaneous design of observers and controllers for a class of piecewise-affine systems against signal quantization occurring in both measurement output and control input channels. The general scenario is considered that system state and estimated state may not be in the same operating region. By a novel quantization-errordependent Lyapunov function, the stability and H∞ performance criteria are first established for the augmented system composed of a closed-loop control system and an estimation error system with the aid of S-procedure involving the region Partition Information of the original system. Then, by the cone complementary linearization algorithm, the desired observer and controller gains are solved simultaneously such that the resulting closed-loop system is asymptotically stable with a prescribed H∞ performance index. Finally, a networked single-link robot arm is utilized to demonstrate the effectiveness of the proposed control strategy.
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A novel control approach for piecewise-affine systems with quantization in both measurement outputs and control inputs
2016 Seventh International Conference on Intelligent Control and Information Processing (ICICIP), 2016Co-Authors: Junnan Shen, Zepeng Ning, Lixian ZhangAbstract:The paper addresses the design problem of piecewise-affine output-feedback controllers for a family of piecewise-affine systems against signal quantization. The quantization is considered to occur in both measurement outputs and control inputs. By constructing a novel quantization-dependent Lyapunov function, the stability and H∞ performance criteria are developed for the closed-loop system with the usage of S-procedure that involves the region Partition Information. Then, the desired controller gains are obtained in order to guarantee that the resulting closed-loop control system is asymptotically stable with a guaranteed H∞ performance index. Finally, a numerical example is provided to show the effectiveness of the proposed control method.
