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International Conference on Multisensor Fusion and Integration for intelligent systems (MFI)

作者： Frederik Beutler Marco F. Huber Uwe D. Hanebeck Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute of Anthropomatics Karlsruhe Institute of Technology Karlsruhe Germany Variable Image Acquisition and Processing Research Group Fraunhofer Institute of Optronics System Technologies and Image Exploitation Karlsruhe Germany

In range-based pose tracking, the translation and rotation of an object with respect to a global coordinate system has to be estimated. The ranges are measured between the target and the global frame. In this paper, an intelligent decomposition is introduced in order to reduce the computational effort for pose tracking. Usually, decomposition procedures only exploit conditionally linear models. In this paper, this principle is generalized to conditionally integrable substructures and applied to pose tracking. Due to a modified measurement equation, parts of the problem can even be solved analytically.

关键词： Mathematical model Equations Noise Noise measurement Coordinate measuring machines Target tracking Covariance matrix

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Fingerprint Watermarking for H.264 Streaming Media

Fingerprint Watermarking for H.264 Streaming Media

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Frontiers in the Convergence of Bioscience and Information Technologies, FBIT

作者： Sooyeun Jung Dongeun Lee Seongwon Lee Joonki Paik Image Processing and Intelligent Systems Laboratory Department of Image Engineering Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea Department of Computer Engineering Kwangwoon University Seoul South Korea

In this paper we propose a method that identifies users at H.264 streaming using watermarking with fingerprints. The watermark can efficiently reduce the potential danger of forgery or alteration. Especially a biometric watermark has various advantages. Among entire biometric characteristics, the fingerprint is the most convenient and economical. In this paper we propose a novel fingerprint-based watermarking technique that can survive under very low bit-rate compression. The proposed algorithm consists of enhancement of a fingerprint image, watermark insertion using discrete wavelet transform. In this paper we also analyze H.264 compression pattern and its effects on watermarking. After restoring the damaged watermark sequence using various filters, the algorithm extracts the embedded watermark. The proposed algorithm can achieve robust watermark extraction against H.264 compressed videos.

关键词： Fingerprint recognition Watermarking Streaming media image coding Biometrics Discrete wavelet transforms Forgery image matching Pattern analysis image restoration

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Optimal stochastic linearization for range-based localization

Optimal stochastic linearization for range-based localizatio...

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2010 IEEE/RSJ International Conference on intelligent Robots and systems

In range-based localization, the trajectory of a mobile object is estimated based on noisy range measurements between the object and known landmarks. In order to deal with this uncertain information, a Bayesian state estimator is presented, which exploits optimal stochastic linearization. Compared to standard state estimators like the Extended or Unscented Kalman Filter, where a point-based Gaussian approximation is used, the proposed approach considers the entire Gaussian density for linearization. By employing the common assumption that the state and measurements are jointly Gaussian, the linearization can be calculated in closed form and thus analytic expressions for the range-based localization problem can be derived.

关键词： Noise Noise level Mathematical model Covariance matrix Noise measurement Kalman filters Position measurement

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Coarse-to-Fine Learning for Single-image Super-Resolution

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IEEE Transactions on Neural Networks and Learning systems 2017年第5期28卷 1109-1122页

作者： Zhang, Kaibing Tao, Dacheng Gao, Xinbo Li, Xuelong Li, Jie School of Computer and Information Science Hubei Engineering University Xiaogan Hubei432000 China Centre for Quantum Computation and Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia State Key Laboratory of Integrated Services Networks School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China State Key Laboratory of Transient Optics and Photonics Xi'An Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an Shaanxi710119 China Video and Image Processing System Laboratory School of Electronic Engineering Xidian University Xi'an Shaanxi710071 China

This paper develops a coarse-to-fine framework for single-image super-resolution (SR) reconstruction. The coarse-to-fine approach achieves high-quality SR recovery based on the complementary properties of both example learning-and reconstruction-based algorithms: example learning-based SR approaches are useful for generating plausible details from external exemplars but poor at suppressing aliasing artifacts, while reconstruction-based SR methods are propitious for preserving sharp edges yet fail to generate fine details. In the coarse stage of the method, we use a set of simple yet effective mapping functions, learned via correlative neighbor regression of grouped low-resolution (LR) to high-resolution (HR) dictionary atoms, to synthesize an initial SR estimate with particularly low computational cost. In the fine stage, we devise an effective regularization term that seamlessly integrates the properties of local structural regularity, nonlocal self-similarity, and collaborative representation over relevant atoms in a learned HR dictionary, to further improve the visual quality of the initial SR estimation obtained in the coarse stage. The experimental results indicate that our method outperforms other state-of-the-art methods for producing high-quality images despite that both the initial SR estimation and the followed enhancement are cheap to implement. © 2012 IEEE.

关键词： Optical resolving power

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The impact of stock-dependent demand on supply chain dynamics

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Applied Mathematical Modelling 2013年第18-19期37卷 8348-8362页

作者： Yongchang Wei Hongwei Wang Chao Qi Institute of Systems Engineering and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Wuhan 430074 PR China School of Business Administration Zhongnan University of Economics and Law Wuhan 430073 PR China

This paper presents an investigation on the dynamics of a supply chain system under stock-dependent demand. Considering the feature of piecewise linearity, a switched linear model composed of three subsystems is developed. Based on the switched model, some analytical stability results are derived. Simulation experiments are designed to verify the stability results and observe nonlinear dynamics. We show that stock-dependent demand not only leads to different stability results but also makes nonlinear dynamics more complicated. We also reveal that the nonlinear dynamics of the switched model, such as chaotic and periodic fluctuations of inventory and order, are essentially caused by switching frequently among subsystems due to uncertainties of inventory status. The results obtained in this paper help us understand the dynamic complexities of supply chain system and provide guidelines for selecting decision parameters to improve overall performance.

关键词： Supply chain system Stock-dependent demand Dynamics Switched system Modeling and simulation

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Fog images Generation About Unmanned Surface Vessels with Improved Generative Adversarial Network

Fog Images Generation About Unmanned Surface Vessels with Im...

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Chinese Control Conference (CCC)

作者： Yifeng Tang Zhihui Huang Chuancong Tang Chuanshang Luo Yifan Xu Bin Liu Hai-Tao Zhang Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation the Engineering Research Center of Autonomous Intelligent Unmanned Systems Wuhan China State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan China

This paper proposes a fog weather data augmentation method for the unmanned surface vessels (USVs) via improved Generative Adversarial Network(GAN) model. First, a generator scheme for GAN is proposed with the guided generation of the atmospheric scattering model in this paper. A Laplacian Pyramid Based Depth Residuals model is added to the generator which reduces the difficulty of generating fog images caused by the degradation of water surface image and improves the quality of generated images. Finally, fog images are generated from sunny weather images collected with HUST-12C by LPBDR-GAN model and experiments show that generated images are very close to real fog images.

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A TDOA/AOA Hybrid Positioning Based on Improved Sparrow Search Algorithm for Mobile Position Estimation

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Wireless Communications and Mobile Computing 2023年第1期2023卷

作者： Hu, Zhongyi Lu, Dongwan Xu, Minghai Tong, Yinsheng Ma, Hanjie Yue, Yinggao School of Computer Science and Artificial Intelligence Wenzhou University Wenzhou325035 China Intelligent Information Systems Institute Wenzhou University Wenzhou325035 China Key Laboratory of Intelligent Image Processing and Analysis Wenzhou China School of Intelligent Manufacturing and Electronic Engineering Wenzhou University of Technology Wenzhou325035 China

To address the difficulty in calculating the nonlinear equation of time difference of arrival (TDOA) positioning, as well as the problem of measurement error in the hybrid time difference of arrival/angle of arrival (TDOA/AOA) positioning algorithm, an improved sparrow search algorithm is proposed to optimize positioning, and the optimization mechanism is retained on the basis of improving the performance of the original algorithm. The maximum likelihood estimation method is used to calculate the objective function, and then, the estimated function of the mobile station is used as the fitness function to generate the initial population of sparrows. Then, using particle swarm optimization, optimize the sparrow search algorithm and obtain the population's optimal solution in order to obtain the optimal position. The simulation results show that, when compared to the existing algorithm, increasing the number of base stations increases the average accuracy of the sparrow search algorithm (SSA) positioning method by 18.54% and 4.5%, respectively, and, when compared to the proposed particle swarm optimization (PSO) positioning method, by 13.79% and 11.6% as the radius increases. The SSA hybrid positioning algorithm performs better in terms of positioning accuracy, convergence speed, and robustness. © 2023 Zhongyi Hu et al.

关键词： Time difference of arrival

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Decentralized adaptive stabilization of nonlinear interconnected stochastic systems by output feedback

Decentralized adaptive stabilization of nonlinear interconne...

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International Conference on Control and Automation (ICCA)

作者： Huijin Fan Li Xu The Key Laboratory of Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology China The Department of Electronics and Information Systems Akita Prefectural University Akita Japan

ISBN: (纸本)9781424447060

This paper studies the stabilization problem for a class of stochastic nonlinear interconnected systems with unknown parameters involved. By employing filtered transformation, the stochastic Lyapunov-like theorem and the back-stepping design technique, a decentralized output-feedback controller and parameter adaptive law are proposed. It is proved that the closed-loop, large-scale, interconnected stochastic systems is globally asymptotically stable in probability.

关键词： Stochastic systems Output feedback Control systems Adaptive control Stochastic processes Interconnected systems Nonlinear systems Programmable control Differential equations Nonlinear control systems

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An adaptive velocity estimation approach for improved disk drive control performance

An adaptive velocity estimation approach for improved disk d...

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Annual Conference of Industrial Electronics Society

作者： F. Janabi-Sharifi A. Shademan Robotics and Manufacturing Automation Laboratory Department of Mechanical AeroSpace and Industrial Engineering Ryerson University Toronto Canada Signal and Image Processing Group School of Intelligent Systems IPM Niavaran Tehran Iran

For disk servo system design, it is desired to optimize data storage and transfer subject to the constraints imposed by the servomechanism including velocity estimation and control algorithm, disk space, the actuator, and other limiting factors. Therefore, positioning the head with high accuracy, speed, and reliability is of significant importance. Since velocity estimation is essential for many disk servomechanisms, the quality of head positioning will be governed by the accuracy, speed and reliability of the velocity estimation methods employed. In this paper, adaptive windowing techniques for discrete velocity estimation in disk drives are introduced. The methods are compared with conventional techniques such as finite difference method and Kalman filtering using the introduced measures. It is shown that the proposed techniques generate relatively accurate and reliable estimates with reduced time delays and lower amplitude distortions when compared with the previous methods. Finally, it is demonstrated that the proposed techniques improve the control performance of the disk servo systems.

关键词： Programmable control Adaptive control Disk drives Velocity control Servomechanisms Control systems Constraint optimization Design optimization Memory Actuators

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A Novel Brain-Inspired Hierarchical Perception-Association Circuit Based on Memristor Arrays

SSRN

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SSRN 2023年

作者： Chen, Liangyu Wang, Xiaoping Chen, Zhanfei Yang, Chao Zeng, Zhigang School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Image Processing and Intelligent Control Education Ministry of China Wuhan430074 China Hubei Key Laboratory of Brain-inspired Intelligent Systems Wuhan430074 China

In the brain, primary sensory cells can efficiently perceive multimodal stimuli, and then associative memory cells perform an advanced bidirectional associative memory function with perceived information. Here, a brain-inspired hierarchical perception-association circuit based on memristor arrays is proposed. Firstly, a memristive reservoir computing circuit is designed to simulate a low-level perceptual function, which mainly comprises dynamic analog reservoirs, memristor arrays, and analog integrators, enabling efficient spatio-temporal information processing. Secondly, a spiking bidirectional associative memory memristive circuit, as the core of the whole circuit, is proposed to mimick a high-level associative function, which mainly consists of memristor arrays, current amplifiers, and leaky integrate-and-fire neuron circuits, implementing multimodal associative learning. The simulation results in LTspice show that the modified neuron circuit exhibits 66× improvement in energy efficiency, and the proposed circuit can precisely perform the letter association and vision-audio association tasks in a spiking fashion with an average firing energy consumption of 230 pJ/spike, which has a great potential to be embedded in mobile robotic platforms. © 2023, The Authors. All rights reserved.

关键词： Memristors

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