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检索条件"主题词=Filtering algorithms"

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Sequential Markov Chain Monte Carlo methods on Matrix Lie Groups

Sequential Markov Chain Monte Carlo methods on Matrix Lie Gr...

引用

International Conference on Information Fusion

作者： Enzo Lopez Karim Dahia Nicolas Merlinge Benedicte Winter-Bonnet Alain Maschiella Christian Musso DTIS ONERA Université Paris-Saclay Palaiseau France MBDA Plessis-Robinson France

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

Particle filters on Lie Groups represent a cutting-edge approach in nonlinear filtering and control. By generating randomly distributed particles from proposed densities, while accurately preserving rotation matrices, they offer a promising solution to nonlinear systems. However, particle filters grapple with numerous challenges such as high computational costs due to the large number of particles needed, vulnerability to particle degeneracy as well as the curse of dimensionality. To address these issues, Sequential Markov Chain Monte Carlo (SMCMC) methods aim to mitigate sensitivity to high-dimensional systems by iteratively sampling from the posterior density of the system state, gradually refining the estimation. In this paper we extend SMCMC techniques to matrix Lie groups, resulting in the Lie Groups Sequential Markov Chain Monte Carlo (LG-SMCMC) filter that circumvent the major drawbacks of particle filters. The proposed approach incorporates enhancements based on the Metropolis-Hastings algorithm, further improving the algorithms efficiency and robustness. To validate the effectiveness of these methods, the algorithms are tested on an Unmanned Aerial Vehicle (UAV) navigation scenario with challenging discrepancies in the noise tuning.

关键词： Monte Carlo methods Sensitivity Noise Refining Lie groups filtering algorithms Autonomous aerial vehicles Particle filters Robustness Tuning

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A Novel Multiobjective Design Technique for LTCC Bandpass Filters with Fractal-Shaped Segments

A Novel Multiobjective Design Technique for LTCC Bandpass Fi...

引用

Electronic Information Engineering and Computer Communication (EIECC), International Conference on

作者： Gongda Hu Yun Ge Yuan He Gang Wang Department of Electronic Engineering and Information Science University of Science and Technology of China Hefei China

ISBN: (数字)9798331534622

ISBN: (纸本)9798331534639

This paper proposes a new technique for designing bandpass filters based on low-temperature cofired ceramic (LTCC) technology. The proposed method innovatively represents the conductor shape contour of the LTCC bandpass filter with nodes and segments. By defining the distributed nodes' positions, the cross-plane line segment structure with fractal shapes, and applying appropriate node connection schemes, A bandpass filtering structure that ensures effective transmission of in-band signals and effective out-of-band suppression can be constructed. By encoding the shape attributes of nodes and line segments, as well as well-defined multiple objective functions, the multiobjective evolutionary algorithm can be utilized for the optimization design for the proposed filter.

关键词： Band-pass filters Shape filtering algorithms Linear programming Search problems Information filters Fractals Encoding Ceramics Optimization

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Detecting Video Image Changes Based on Improved Difference Map and Image Fusion

Detecting Video Image Changes Based on Improved Difference M...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Ang Tian Zhenhong Jia Xiaohui Huang Sensen Song Jiajia Wang Gang Zhou Fei Shi School of Computer Science and Technology Xinjiang University Xinjiang China Key Laboratory of Signal Detection and ProcessingXinjiang University Xinjiang China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

To resolve the problems of complex random noise and poor image quality in hawk-eye surveillance video images under low illumination, a surveillance video image change detection method based on K-means clustering and differential image adaptive fusion was developed. First, the log ratio operator and extreme average ratio operator were used to obtain two difference maps for two video surveillance images at different times. Then, the Laplacian pyramid was used for adaptive fusion. Next, the TVL1 dual method was used to denoise the fused image, PCA was used to fuse the denoised image and the enhanced image of the changed region, and then the adaptive median filter was used for filtering. Finally, the two-stage clustering method was used to obtain the final change detection results for the difference map. Based on our experimental findings, our method outperforms comparative algorithms in many metrics, including accuracy, robustness, time consumption, and false alarm rate.

关键词： Laplace equations Fuses Noise Lighting Clustering algorithms Adaptive filters filtering algorithms

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A Simple and Accurate PPG Systolic Peak Detector Based on Fractional Order Calculus

A Simple and Accurate PPG Systolic Peak Detector Based on Fr...

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International Artificial Intelligence and Data Processing Symposium (IDAP)

作者： Salah Ferdi Fayçal Abdelliche National Polytechnic School of Constantine Constantine Algeria

ISBN: (数字)9798331531492

ISBN: (纸本)9798331531508

Accurate detection of systolic peaks in photoplethysmogram (PPG) signals using simple algorithms is crucial for many healthcare monitoring systems, especially in wearable devices. This paper presents a simple yet accurate systolic peak detector that employs a fractional-order calculus-based filter, performing both noise removal and inflection/extrema point detection in a single stage. The proposed filter can detect inflection and extrema points even in highly noisy PPG signals. By correctly detecting systolic peaks, other fiducial points can be easily identified and subsequent accurate measurements such as heart rate can be obtained. The proposed method was validated on the CapnoBase benchmark dataset, demonstrating an overall accuracy sensitivity, precision and F1-Score of 99.62%, 99.89%, 99.52%, 99.70% respectively for a tolerance interval of 30 ms. These results are comparable to those achieved with state-of-the-art methods, while the proposed method offers the advantage of simpler implementation.

关键词： Performance evaluation Accuracy Sensitivity Noise Detectors Medical services filtering algorithms Noise measurement Wearable devices Monitoring

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Two Wheeled Self Balancing Vehicle Based on Wireless Remote Control

Two Wheeled Self Balancing Vehicle Based on Wireless Remote ...

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IEEE International Conference on Electronic Information and Communication Technology (ICEICT)

作者： Shuhua Li Xindong Huang Shaokang Zhou Dun Mao Hongkai Nian School of Opto-Electronic and Communication Engineering Xiamen University of Technology Xiamen China Fujian Zhengtai Judicial Expertise Center Xiamen China

ISBN: (数字)9798350384437

ISBN: (纸本)9798350384444

A design scheme of a two wheeled self balancing vehicle with wireless remote control is proposed. STC8G2K64S4 is used as the main controller of the system, the angle and acceleration information of the vehicle is obtained by gyroscope and accelerometer, the actual angle of the vehicle is fused by using complementary filtering algorithm, and after being processed by PID algorithm, the microcontroller outputs a PWM control signal to control the motor of the vehicle, so as to make the vehicle keep balance. The experimental results show that the design scheme can keep the vehicle upright and has a certain anti-jamming ability, and can control the motion state of the vehicle in real time through the handheld remote control, stable forward, backward and steering.

关键词： Wireless communication Software design Welding Process control Debugging filtering algorithms Real-time systems

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An Improved Method for Designing MTD Filter Coefficients Based on Second-Order Cone Programming

An Improved Method for Designing MTD Filter Coefficients Bas...

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Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Hao He Shao Qiang Chang Yan Zi Han Quan Hua Liu Wen Xin Guan School of Information and Electronics Beijing Institute of Technology Beijing China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

To improve the convergence performance of filter coefficient solving processes, align the filter frequency response curve more closely with the desired frequency response curve, and enhance the robustness of the filter coefficient solving method, this paper proposes an improved MTD filter coefficient solving method based on second-order cone programming. This method can achieve a filter frequency response that closely aligns with the desired frequency response. The effectiveness of the method is verified through simulation experiments and actual measured data.

关键词： filtering algorithms Programming Information filters Linear programming Data processing Frequency response Robustness Doppler effect Clutter Convergence

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Multi-Scale 3D Gaussian Splatting for Anti-Aliased Rendering

Multi-Scale 3D Gaussian Splatting for Anti-Aliased Rendering

引用

Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zhiwen Yan Weng Fei Low Yu Chen Gim Hee Lee Department of Computer Science National University of Singapore

ISBN: (数字)9798350353006

ISBN: (纸本)9798350353013

3D Gaussians have recently emerged as a highly efficient representation for 3D reconstruction and rendering. Despite its high rendering quality and speed at high resolutions, they both deteriorate drastically when rendered at lower resolutions or from far away camera position. During low resolution or far away rendering, the pixel size of the image can fall below the Nyquist frequency compared to the screen size of each splatted 3D Gaussian and leads to aliasing effect. The rendering is also drastically slowed down by the sequential alpha blending of more splatted Gaussians per pixel. To address these issues, we propose a multi-scale 3D Gaussian splatting algorithm, which maintains Gaussians at different scales to represent the same scene. Higher-resolution images are rendered with more small Gaussians, and lower-resolution images are rendered with fewer larger Gaussians. With similar training time, our algorithm can achieve 13%-66% PSNR and 160%-2400% rendering speed improvement at 4 × -128 × scale rendering on Mip-NeRF360 dataset compared to the single scale 3D Gaussian splatting. More results and code are released on our project page.

关键词： Training Degradation Computer vision Three-dimensional displays Image resolution Codes filtering algorithms

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Distributed Energy Resources with LCL Filter Control and Protection Using Model Predictive Control

Distributed Energy Resources with LCL Filter Control and Pro...

引用

IEEE International Conference on Automatica (ICA-ACCA)

作者： Dave Figueroa Jaime Guzmán Ignacio A. Acosta Reinier López Ahuar Ricardo Pérez-Ibacache César A. Silva Electronics Department Universidad Técnica Federico Santa María Valparaíso Chile The Thinking Pod Innovations Ltd Nottingham England

ISBN: (数字)9798350378115

ISBN: (纸本)9798350378122

In this paper, a primary Model-based Predictive Control (MPC) for Distributed Energy Resources (DERs) is studied. This primary control regulates voltage and frequency, and has the capacity to set a predefined operation point while simultaneously imposing security constraints on the inverter’s output current. To achieve these objectives, the MPC takes into account the LCL filter dynamics to increase the prediction accuracy of the system. The MPC algorithm is formulated as a Quadratic Programming (QP) problem which is solved using a first-order optimization method. To validate this approach, simulation results using MATLAB/SIMULINK and PLECS are presented. The results confirm the efficacy of the proposed primary control method.

关键词： Simulation filtering algorithms Predictive models Prediction algorithms Distributed power generation Security Quadratic programming Voltage control Protection Predictive control

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Research on INS/GNSS Integrated Navigation algorithms Assisted by Neural Networks

Research on INS/GNSS Integrated Navigation Algorithms Assist...

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Computer Science and Blockchain (CCSB), International Conference on

作者： Heng Wang Weifeng Li Navigation College Dalian Maritime University Dalian China

ISBN: (数字)9798350356502

ISBN: (纸本)9798350356519

With the rapid advancement of modern science and technology, navigation systems have garnered widespread attention due to their high precision, high dynamics, and high reliability. Integrated navigation systems, composed of Inertial Navigation Systems (INS) and Global Navigation Satellite Systems (GNSS), are widely used in maritime navigation. Improving the accuracy of these systems has been a major focus for researchers both domestically and internationally. In adverse weather conditions, GNSS receivers experience significant accuracy degradation due to electromagnetic interference and signal blockage, leading to filter divergence and severe deterioration in performance when operating in pure inertial mode. To address this issue, an improved Radial Basis Function (RBF) neural network enhanced by Particle Swarm Optimization (PSO) is introduced for auxiliary filtering. [1] [2] With this algorithm, high robustness and seamless navigation can still be achieved even when GNSS signals are completely lost.

关键词： Degradation Global navigation satellite system Accuracy filtering Neural networks Transportation Inertial navigation filtering algorithms Robustness Kalman filters

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Recursive and Nonrecursive Passive Target Localization algorithms with Bearing-Only Measurements

Recursive and Nonrecursive Passive Target Localization Algor...

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Ocean Studies (ICOS), International Conference on

作者： O.A. Stepanov V.P. Zolotarevich M.S. Ivanov A.V. Motorin ITMO University Concern CSRI Elektropribor JSC St. Petersburg Russia

ISBN: (数字)9798331532307

ISBN: (纸本)9798331532314

The paper investigates the problem of passive target localization from a moving observer using bearing-only measurements. The following three estimation algorithms are considered: a recursive iterative extended Kalman smoother; a nonrecursive iterative batch linearized filter, and a recursive iterative batch linearized smoother. The accuracy and computational complexity of the recursive and nonrecursive algorithms are compared using the Monte Carlo simulation. The Cramer-Rao lower bound for the problem under consideration is calculated. The advantages of the recursive iterative batch linearized smoother over the nonrecursive iterative batch linearized filter and the recursive iterative extended Kalman smoother are shown.

关键词： Location awareness Accuracy Software algorithms Estimation Sea measurements filtering algorithms Observers Iterative algorithms Trajectory Kalman filters

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