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检索条件"主题词=Filtering algorithms"

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A 6.0-to-6.9GHz 99fsrms-Jitter Type-II Sampling PLL with Automatic Frequency and Phase Calibration Method Achieving 0.62μs Locking Time in 28nm CMOS

A 6.0-to-6.9GHz 99fsrms-Jitter Type-II Sampling PLL with Aut...

引用

Custom Integrated Circuits Conference (CICC)

作者： Jian Yang Tailong Xu Xi Meng Zhenghao Li Jun Yin Pui-In Mak Rui P. Martins Quan Pan Southern University of Science and Technology Shenzhen China University of Macau Macau China Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal

ISBN: (数字)9798350394061

ISBN: (纸本)9798350394078

The settling time of a frequency synthesizer plays a crucial role in determining the dynamic performance of modern wireless and wireline systems which employ power gating and dynamic voltage frequency scaling techniques to reduce power dissipation. The all-digital phase-locked loop (ADPLL), with its digital loop filter (LF), emerges as a superior alternative to the analog PLL since its swift convergence speed and compatibility with digital algorithms. The counter-based ADPLL [1], depicted in Fig. 1 (top-left), can accelerate the locking speed by configuring the digital loop filter in the type-I mode to search the coarse-band switched capacitor control word rapidly. However, a phase offset exists between the REF and D/V clocks after the type-I loop settles, which prolongs the locking time when the loop filter is switched back to the type-II mode for phase locking. To address this limitation, the type-II digital PLL employs frequency and phase locking loop techniques, such as frequency aid [2], [3], tuning word estimation [4], gearshift, and fast-Fourier transform techniques [5], [6], to accelerate the settling process. However, these approaches require a digital loop filter with flexible programmability. Thus, the fast-locking techniques developed for digital PLLs cannot be directly mitigated to the low-jitter type-II sampling PLL [7] using a high-gain but narrow-capture-range sampling phase detector (PD) and a limited programmable analog loop filter. The typical long-time frequency locking behavior is depicted in Fig. 1 (top-right). Even after achieving frequency lock, the out-of-capture range in the phase locking process still results in a long iteration time, as shown by the dashed line in Fig. 1 (bottom-right).

关键词： Wireless communication Time-frequency analysis Frequency synthesizers Switches Transforms filtering algorithms Frequency estimation

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Efficient Monitoring of CPS and IoT Systems: A Deployment Guide for Empirical Evaluations

Efficient Monitoring of CPS and IoT Systems: A Deployment Gu...

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Mediterranean Conference on Embedded Computing (MECO)

作者： Jan Körner Samuel Bach Albin Karlsson Linus Sundkvist Romaric Duvignau Department of Computer Science and Engineering Chalmers University of Technology and University of Gothenburg Gothenburg Sweden

ISBN: (数字)9798350387568

ISBN: (纸本)9798350387575

As the digitalization of our world continues, the volume of data produced escalates rapidly. Communication often constitutes the most energy-intensive aspect of applications, making it a prime target for optimization. This paper studies the efficiency and precision of monitoring Cyber-Physical Systems (CPS) and Internet of Things (IoT) devices in real experimental deployment scenarios. We evaluate in this work the performance of six different monitoring algorithms concerning CPU utilization, memory usage, network traffic, energy consumption, and monitoring accuracy. Our experimental setup is a network consisting of 38 Raspberry Pis connected to a single host computer via Ethernet. Monitoring was conducted both on the devices themselves and on the host computer, which served as the metrics-receiving stack. We offer here a comprehensive deployment guide serving as a valuable resource for reproducing similar monitoring experiments on IoT devices. Additionally, our own empirical evaluation indicate notable differences among the tested algorithms, highlighting the importance of application constraints on the selection of a monitoring algorithm. Seeking those real-world experiments aim to add substantial value to existing surveys by offering deeper insights, practical findings and empirical evidence.

关键词： Surveys Performance evaluation Energy consumption Memory management Telecommunication traffic Ethernet filtering algorithms

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Research on Underwater Integrated Navigation Based on Distance Constraint

Research on Underwater Integrated Navigation Based on Distan...

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IEEE Advanced Information Management,Communicates,Electronic and Automation Control Conference (IMCEC)

作者： Hongwei Wei Huaiyi Guan Bao Li Jun Fu College of Electrical Engineering Naval University of Engineering Hubei China

ISBN: (数字)9798350316537

ISBN: (纸本)9798350316544

Integrated navigation with DVL and SINS can improve the positioning accuracy of UUV, but the work of DVL will destroy the concealment of UUV. The distance measured by underwater acoustic has a high accuracy, and does not significantly reduce the concealment of UUV. This paper proposed an underwater integrated navigation algorithm based on distance constraints and UBB-filter. Then, we verify the effectiveness of the method through simulation experiments. The results show that the method proposed in this paper has higher accuracy than the traditional KF based integrated navigation method. With the new method, the positioning error is reduced by 67.3%. The method proposed in this paper provide a new way of thinking for underwater integrated navigation, and this algorithm is effective.

关键词： Accuracy Automation Navigation Gaussian noise filtering algorithms Acoustic measurements Mathematical models

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Feature estimation and parameter tuning using H∞ Filter on FastSLAM framework

Feature estimation and parameter tuning using H∞ Filter on ...

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International Conference on Energy, Power and Environment: Towards Sustainable Growth (ICEPE)

作者： Varanasi Radhika Shreya Arnav Mishra Koena Mukherjee Department of Electronics and Instrumentation Engineering National Institute of Technology Silchar Silchar Assam India

ISBN: (数字)9798350379297

ISBN: (纸本)9798350379303

Simultaneous Localization and Mapping (SLAM) plays a key role in enabling mobile robots to autonomously navigate and build a map of their environment. Despite its wide range of applications, localization and mapping has its own disadvantages which include computation, feature representation,sensor noise, data association and robustness in dynamic environments. EKF-SLAM and FastSLAM are two frameworks of SLAM. However, they face problems related incorrect priori knowledge of mean, correlation and covariances of process as well as measurement noise as Kalman Filter acts as a minimum covariance estimator. In this paper an Extended H-infinity based FastSLAM is proposed which takes into consideration worst case minimization error and priori knowledge of noise is not essential. The proposed framework is an integration of Rao-Blackwellization Particle filter for proposal distribution and robot pose estimation along with Extended H-Infinity Filter for feature/landmark estimation. Further, the impact of the tuning parameter θ on accuracy is tested. The proposed algorithm is evaluated on a simulated environment and is compared with the existing frameworks.

关键词： Location awareness Simultaneous localization and mapping Accuracy Noise H infinity control filtering algorithms Particle filters

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Multi-Sensor Fusion Floor Location Method Based on Extended Kalman Algorithm

Multi-Sensor Fusion Floor Location Method Based on Extended ...

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Robotics, Automation and Artificial Intelligence (RAAI), IEEE International Conference on

作者： Zihao Gao Yuhan Zhou Jianhong Liang Xinyu Liu Siyan WU Mohan Rui Simeng Lv Jinguo Huang School of Mechanical Engineering and Automation Beihang University Beijing University of Posts and Telecommunications Beijing China School of Intelligent Engineering and Automation Beijing University of Posts and Telecommunications Beijing China School of Mechanical Engineering and Automation Beihang University Beijing China International School Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798331520038

ISBN: (纸本)9798331520045

This paper investigates an extended Kalman filter-based barometer and IMU fusion floor localization method, aiming to solve the problem of precise floor localization for mobile robots that need to take elevators. By establishing an index between spatial height and floor levels, the paper uses the extended Kalman algorithm to fuse filtered IMU acceleration data with barometric data optimized by the least squares method to obtain the robot's height data. Subsequently, the robot's floor data is obtained based on the floor index. Experiments show that the comprehensive height prediction error of this paper is within 0.10m, and the floor prediction accuracy reaches 98%. The research provides effective technical support for floor localization of mobile robots in elevator scenarios.

关键词： Location awareness filtering algorithms Sensor fusion Prediction algorithms Elevators Kalman filters Mobile robots Indexes Floors Least mean squares methods

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Estimation of QT Interval Duration Using a Modernized Wavelet Transform based on Gauss-Hermite Functions

Estimation of QT Interval Duration Using a Modernized Wavele...

引用

Information, Control, and Communication Technologies (ICCT), International Conference on

作者： Balakin Dmitry Alali Charif Department of Fundamentals of Radio Engineering Moscow Power Engineering Institute Moscow Russia

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

The relevance of developing new algorithms for diagnosing cardiovascular diseases is due to the fact that these diseases are the leading cause of death worldwide. One form of potential disease is an increase in the QT interval, which can be a harbinger of cardiac arrest or sudden death. Therefore, it is important not only to diagnose the presence of an elongated QT interval, but to timely detect a trend to this, thereby making a forecast about a person's condition in the future. The article describes the basic principles of constructing an algorithm for tracking the trend to an increase in the QT interval. The algorithm is based on the wavelet transform, where the Gauss- Hermite functions act as a basis. The wavelet transform is interpreted as correlation processing, and due to the ability to change the scale of the basis functions, it is possible to track the dynamics of changes in the duration of the QT interval. The result of such processing is a diagnostic function that is similar to a rhythmogram, where the ECG signal time is plotted along the abscissa axis, and the duration of the QT interval is plotted along the ordinate.

关键词： Wavelet transforms Matched filters Correlation Heuristic algorithms Noise Estimation Electrocardiography filtering algorithms Market research Information filters

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Enhancing Change Detection Robustness: A Whitening Transformation Approach

Enhancing Change Detection Robustness: A Whitening Transform...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Fei Liang Qi Zang Zhengyao Wang Yang Hu Dou Quan Shuang Wang School of Artificial Intelligence Xidian University Shaanxi China Aerial Photography and Remote Sensing Group Co. Ltd. Xi’an China

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

The vast amount of remote sensing data has been instrumental in supporting research on change detection algorithms based on deep ***, factors such as geographical changes and variations in sensor parameters can result in significant style differences between remote sensing images at different time points, leading to a decline in model *** address this issue, this paper proposes a change detection algorithm based on whitening feature extraction, aiming to alleviate distribution differences by decoupling domain-invariant discriminative features from domain-specific style *** effectiveness of the proposed method is demonstrated through transfer experiments from the SVCD dataset to the SZADA dataset and from the SYSU dataset to the SZADA dataset.

关键词： Instruments filtering algorithms Feature extraction Information filters Robustness Data models Sensors

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Adaptive Estimation of Multiple Fading Factors Based on RGAM Model

Adaptive Estimation of Multiple Fading Factors Based on RGAM...

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International Joint Conference on Neural Networks (IJCNN)

作者： Hongfu Xu Haiyong Luo Zijian Wu Fang Zhao Changhai Lin School of Computer Science Beijing University of Posts and Telecommunications Beijing China Institute of Computing Technology Chinese Academy of Sciences Beijing China Yibin Tinno Communication Co. Ltd Yibin China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

When there exists a mismatch between the system model or inaccuracies in the statistical characteristics of the noise, it can directly impact the accuracy of current state estimation and potentially lead to filter divergence. In the domain of dynamic positioning and navigation, the Kalman filter has been proposed as a solution to address these issues by incorporating fading factors. Unlike conventional methods for estimating fading factors, this study introduces the RGAM (Resnet Global Attention Mechanism) algorithm model to estimate multiple fading factors associated with state prediction covariance. The RGAM algorithm model leverages the robust estimation capability of network models to accurately estimate the fading factors corresponding to relevant epochs. To validate the effectiveness of the proposed algorithm, experiments were conducted using an actual road data set within the context of a GNSS/INS (Global Navigation Satellite System/ Internal Navigation System) integrated system. Through these experiments, it was observed that employing a filter with accurate fading factors facilitates the avoidance of filter divergence and achieves stable filtering performance in the integrated system.

关键词： Fading channels Adaptation models Accuracy filtering Roads Predictive models filtering algorithms

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Perceptual Encoding Optimization Algorithm Guided by Human Eye Focusing Mechanism

Perceptual Encoding Optimization Algorithm Guided by Human E...

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International Conference on Cybernetics, Robotics and Control (CRC)

作者： Xinran Wan Huiping Deng Sen Xiang School of Information Science and Engineering Wuhan University of Science and Technology Wuhan China

ISBN: (数字)9798331517489

ISBN: (纸本)9798331517496

Perceptual coding algorithms play a crucial role in eliminating visual redundancy in video compression. Despite their promising results, there remains potential for further optimization, particularly in leveraging human visual characteristics for rate control and effectively applying just noticeable distortion (JND)a threshold defining human visual sensitivity to changes. In this paper, we propose a novel HEVC rate control scheme inspired by the focusing mechanism of the human visual system (HVS). By integrating saliency and focal distance information, we construct a focusing factor and incorporate it into the encoding framework. This focusing factor serves as a key parameter for rate control, optimizing LCU-level bit allocation and enhancing video coding efficiency. Furthermore, we combine the focusing factor with a JND-based model to design a Gaussian filter that smooths nonfocused areas, reducing background redundancy while enhancing visual quality. The proposed algorithm is implemented on HM16.7, and experimental results show bitrate savings and PSNR improvements ranging from 0.1 to 0.5 dB compared to state-of-the-art algorithms. Additionally, subjective evaluations confirm significantly enhanced visual quality at equivalent bitrates.

关键词： Video coding Visualization Bit rate Redundancy Focusing filtering algorithms Visual systems Distortion Encoding Optimization

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Extended Information Filter Based on Maximum Correntropy Criterion with Student’s t Kernel Function

Extended Information Filter Based on Maximum Correntropy Cri...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Teng Liu Xiaoliang Feng School of Electrical Engineering Shanghai Dianji University Shanghai China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

This paper addresses the issue of information filtering for nonlinear systems with Student’s t noise interference. In the information filter framework, a new non-Gaussian extended information filter is developed under the MC criterion with Student’s t kernel function (TMCEIF). Firstly, the maximum correntropy (MC) filtering performance criterion with Student’s t kernel function (StKF) is defined. By comparing the Gaussian kernel function and adjusting the kernel bandwidth of the StKF, the StKF decays to zero more slowly for the large error, when the freedom degrees are small. Secondly, the MC criterion with the StKF is applied to design the new extended information filter (EIF). The robustness of the algorithm is verified by the final numerical simulation.

关键词： Automation Noise Interference Bandwidth filtering algorithms Information filters Numerical simulation

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