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检索条件"主题词=Filtering algorithms"

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Research on Localization algorithms for Mobile Robots Based on Laser and Inertial Navigation Fusion

Research on Localization Algorithms for Mobile Robots Based ...

引用

Robotics, Control and Automation Engineering (RCAE), International Conference on

作者： Zhao Liang Zhou Shenghao Shi Weiguang School of Mechanical Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350355642

ISBN: (纸本)9798350355659

This paper primarily investigates localization algorithms for mobile robots based on laser reflectors. It proposes an ICP (Iterative Closest Point) laser odometry method based on sparse point clouds from reflectors, which provides motion updates for the particle set. Continuous localization of the mobile robot is achieved through particle filtering. Experimental comparisons indicate that this localization algorithm has high positioning accuracy and strong robustness against abnormal interference.

关键词： Location awareness Accuracy Service robots filtering Heuristic algorithms Interference filtering algorithms Stability analysis Robustness Mobile robots

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A comparative study on human motion smoothing filters for RGB-D camera teleoperation

A comparative study on human motion smoothing filters for RG...

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International Conference on Mechatronics and Machine Vision in Practice (M2VIP)

作者： Zixiong Wang Yinlong Zhang Xin Zhang Shenyang Institute of Automation (SIA) Chinese Academy of Sciences Shenyang China School of Computing University of Portsmouth Portsmouth UK

ISBN: (数字)9798350391916

ISBN: (纸本)9798350391923

RGB-D camera teleoperation is a promising marker-free method to control robots by capturing human motion. However, the motion-captured data tends to oscillate significantly, leading to a significant deviation in a single step, which cannot be directly used to control the robot in Cartesian space in real time. This paper comprehensively evaluated time-series data filter algorithms to alleviate the data oscillation issue. We compared eight mainstream filters, namely the Savitzky-Golay (S-G) filter, hierarchical threshold filter, median filter, Whittaker filter, weighted sliding convolutional averaging (WSCA) filter, adaptive filter, Kalman filter, and locally estimated scatterplot smoothing filter, with four performance merits (time complexity, mean absolute error (MAE), variance (VAR), and root-mean-square error (RMSE)). Here, the YOLOv8-pose human skeleton recognition algorithm was employed to test different filters due to the excellent motion-capture performance. We conducted 12 groups of human-motion experiments with circular trajectories. The results indicated that the S-G filter excelled in data smoothing with a 26.74% improvement, followed by the WSCA filter with a 24.4% improvement. Meanwhile, the time complexity of the S-G and WSCA algorithms was lower than that of the other six filters. Furthermore, we tested these two algorithms in handwritten teleoperation. The results demonstrated that the filtered trajectory was smooth for the handwritten tasks and verified the effectiveness of the SG and WSCA filter algorithms.

关键词： Robot motion Smoothing methods Robot vision systems Adaptive filters filtering algorithms Aerospace electronics Cameras Trajectory Time complexity Oscillators

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MLCFSM: Multi-Layer Common Feature Selection Methods for Robust Intrusion Detection in IoT Network

MLCFSM: Multi-Layer Common Feature Selection Methods for Rob...

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IEEE International Conference on Emerging & Sustainable Technologies for Power & ICT in a Developing Society (NIGERCON)

作者： Ogobuchi Daniel Okey Demostenes Zegarra Rodrigues João Henrique Klenschmidt Center for Engineering Modelling and Applied Social Sciences Federal University of ABC São Paulo Brazil Department of Computer Science Federal University of Lavras Minas Gerais Brazil

ISBN: (数字)9798331542559

ISBN: (纸本)9798331542566

This paper examines the crucial role of feature selection (FS) methods in enhancing IDS models within IoT security frameworks. With IoT devices generating vast and diverse data, traditional IDS models face the problem of having too many dimensions or data feature space, which hinders their effectiveness. Utilizing FS methods becomes imperative to streamline datasets, improving model performance, and strengthening security measures. The proposed method combines the strengths of filter and wrapper methods to create a subset feature dataset. Initially, three filter methods, including fast correlation-based feature (FCBF), mutual information (MI), and ANOVA F-test (ANOVA), as well as one wrapper method, Forward Sequential FS (FSFS), are applied to the entire dataset to select important features by ranking. We identify the common features in the filter and wrapper methods by constructing an intersection subset. The final feature subset dataset is used to train the proposed MLCFSM (Multi-Layer Common Feature Selection Methods) using 10 classifier algorithms and evaluated on three datasets: FLNET2023, ACI-IoT2023, and CIC-IoT2023. The MLCFSM demonstrates significantly improved performance in terms of the evaluation metrics, achieving up to 99.999% mean accuracy and reduction in computation cost. By reducing dataset dimensionality through MLCFSM, our method demonstrates a competitive performance with state of the art even while using a small feature space.

关键词： Performance evaluation Intrusion detection filtering algorithms Feature extraction Information filters Data models Internet of Things Security Analysis of variance Mutual information

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Research on Centralized and Automatic Control of Filter Rod Conveying in Wrapping Workshop

Research on Centralized and Automatic Control of Filter Rod ...

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International Conference on Artificial Intelligence and Computer Information Technology (AICIT)

作者： Xingke Li Anqi Hu Delun Shi Zhenan Yu Hao Pang Qian Xie Wuhan Cigarette Factory China Tobacco Hubei Industrial Co. Ltd Wuhan China

ISBN: (数字)9798350365443

ISBN: (纸本)9798350365450

This paper explores the research and implementation of an Information Technology (IT) and Operational Technology (OT) integration upgrade for the filter rod conveying process in cigarette packing workshops. By centralizing control over filter rod exchange stations, receivers, emitters, and unloading machines, and using industrial Ethernet for device interconnectivity, the system consolidates data from individual machines through an edge controller. This data is then stored, analyzed, and presented by the cigarette packing data acquisition system. The goal is to achieve comprehensive real-time monitoring of filter rod production and equipment information. Intelligent analysis algorithms enable real-time processing of data from the filter rod conveying process and its associated equipment. Based on these analyses, the system automatically adjusts equipment parameters and operating states, reducing equipment failure rates and filter rod losses during production. Furthermore, real-time monitoring and early warning capabilities improve the system's ability to detect and respond to equipment failures or abnormalities, effectively reducing downtime and maintenance costs.

关键词： Conferences Production Receivers Ethernet filtering algorithms Information filters Real-time systems Maintenance Information technology Wrapping

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DAC Element Mismatch Shaping algorithms in Incremental Delta-Sigma ADCs

DAC Element Mismatch Shaping Algorithms in Incremental Delta...

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IEEE International Symposium on Circuits and Systems (ISCAS)

作者： Omar Ismail Paul Kaesser John G. Kauffman Maurits Ortmanns Institute of Microelectronics University of Ulm Ulm Germany

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Element mismatch error shaping had been thoroughly studied in free-running Delta-Sigma (DS) ADCs, which enabled using multi-bit quantizer in the loopfilter while shaping the non-linearity errors of the feedback DAC unit element mismatch. A popular shaping technique in free-running DS ADCs is the simple rotational data-weighted averaging (DWA), which was shown to be ineffective in state of the art (SoA) higher order incremental Delta-Sigma (I-DS) ADCs. Hence, prior SoA proposed smart shaping techniques tailored for I-DS ADCs, though adding significant area and power complexity compared to DWA. In this work it is shown that by applying periodic reset to the DWA’s rotation index renders it very feasible and effective for DAC mismatch shaping even in higher order I-DS ADCs without the need of changed algorithms.

关键词： Circuits and systems Linearization techniques filtering algorithms Robustness Complexity theory Indexes

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A Method for Identifying Line Losses in Low Voltage Stations in Mountainous Areas under Distributed Photovoltaic Access

A Method for Identifying Line Losses in Low Voltage Stations...

引用

Energy, Power and Electrical Technology (ICEPET), International Conference on

作者： Nanchuan Zhang Zhisong Xu Xiaoyun Mi Yonghang Wang Chengjiao Zhong Di Zhai Liangwei Jia Yi Zhang Shiyu Yang Jie Li Lianli Li Yumei Yang Yuxi Power Supply Bureau Yunnan Power Grid Co. Ltd. Yuxi China

ISBN: (数字)9798350352658

ISBN: (纸本)9798350352665

Due to the integration of distributed photovoltaics, the instantaneous changes in load in low-voltage substations increase, making it more difficult to analyze load variables and increasing the error in line loss identification. Therefore, a method for identifying line losses in low-voltage substations in mountainous areas under distributed photovoltaics integration is proposed. After standardizing the line loss of low-voltage substations in mountainous areas, the bilateral total variation filtering algorithm is used to denoise the line loss data, in order to improve the quality of the line loss data. By combining wavelet analysis with artificial neural networks, a wavelet neural network recognition model is constructed, and the denoised line loss data is input into the recognition model to complete the identification of line loss in low voltage substations in mountainous areas. The experimental results show that compared with other existing methods, the RMS error of line loss identification of the proposed method is the smallest under different number of samples. Therefore, it shows that the line loss identification performance of this method is good.

关键词： Photovoltaic systems Low voltage Analytical models Substations Accuracy filtering algorithms Wavelet analysis

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Weighted Filtered-Enabled BPS Algorithm for PCS-64QAM Transmission System

Weighted Filtered-Enabled BPS Algorithm for PCS-64QAM Transm...

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Asia Communications and Photonics Conference and Exhibition (ACP)

作者： Zhongliang Sun Jinlong Wei Jianwei Tang Linsheng Fan Junpeng Liang Hao Shi Yaguang Hao Tonghui Ji Zhaopeng Xu Weisheng Hu Peng Cheng Laboratory ShenZhen China

Weighted filter-enabled blind phase search (BPS) algorithm variants are experimentally investigated for the PCS-64QAM transmission system. Results validate that the mutual information (MI) performance can be significa... 详细信息

ISBN: (数字)9798350379266

ISBN: (纸本)9798350379273

关键词： Optical filters Asia filtering algorithms Information filters Optical fiber communication Mutual information Photonics

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Extended Target Tracking with 3D-INSEG and its Benefits in Dense Scenarios

Extended Target Tracking with 3D-INSEG and its Benefits in D...

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International Conference on Information Fusion

作者： Nicolás Fierro Martin Adams Leonardo Cament Department of Electrical Engineering Universidad de Chile Santiago Chile

ISBN: (数字)9781737749769

ISBN: (纸本)9798350371420

In Multiple Extended Object Tracking (MEOT), it is assumed that a solitary target can produce multiple measurements. The quality of these measurements is paramount for obtaining accurate estimates of tracks over time. To test state-of-the-art MEOT algorithms, both simulated and real laser data, recorded in open spaces, have been used. MEOT algorithms work well in these scenarios, but when applied in more cluttered or restricted spaces, they often fail to produce good results, because close proximity target measurements are considered as measurements with the same origin. To address these cases, this article applies the 3D INstance SEGmentation (3D-INSEG) algorithm to MEOT to process stereo image sequences, extracting 3D information corresponding to each detected target using cameras. The algorithm selects pixels from each detected target and calculates the disparity map from stereo pairs, projecting them into 3D space using this disparity map. Subsequently, these measurements undergo processing by an extended target Poisson multi-Bernoulli mixture (PMBM) filter with a gamma Gaussian inverse-Wishart (GGIW) implementation. The advantages of MEOT with the 3D-INSEG-generated data are demonstrated in this article via a comparison with MEOT based on Velodyne LiDAR data points recorded from the same scenario processed by the same MEOT algorithm.

关键词： Instance segmentation Target tracking Three-dimensional displays Laser radar Measurement by laser beam Object detection filtering algorithms Time measurement Object tracking Laser fusion

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Numba-Based Non-Local Means Filter for SAR Image Denoising

Numba-Based Non-Local Means Filter for SAR Image Denoising

引用

International Conference on Computer and Automation Engineering, ICCAE

作者： G Devendhar Pratibha Singh Rakesh Sharma Dept. of Electronics and Communication Engg. National Institute of Technology Hamirpur Himachal Pradesh India

ISBN: (数字)9798350370058

ISBN: (纸本)9798350370164

Synthetic Aperture Radar (SAR) images are an essential tool for earth observation and remote sensing, but speckle can degrade the quality of such images. Image processing techniques such as filtering and averaging can effectively reduce the impact of noise on images. This paper evaluates the performance of the hybrid nonlocal means (NLM) filter in denoising Sentinel-1 SAR images. The proposed approach combines adaptive exponential kernel-based pre-processing with an NLM filter. The NLM algorithm is computationally intensive and time-consuming due to its pixel-by-pixel denoising based on extended neighborhood similarities. To address this challenge, this paper explores parallelization of the NLM algorithm using NUMBA, a Python compiler, to accelerate its performance. It is found that the proposed approach shows a significant improvement in terms of Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index (SSIM), and Mean Squared Error (MSE) and performs better than conventional NLM filters and even provides the greatest speedup when compared to earlier parallel NLM techniques.

关键词： PSNR filtering Noise reduction filtering algorithms Speckle Radar polarimetry Indexes

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Diagnosis of Dyslexia using 2D EEG Feature Map and Convolutional Neural Network

Diagnosis of Dyslexia using 2D EEG Feature Map and Convoluti...

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Medical Technologies National Conference (TIPTEKNO)

作者： Ozlem Karabiber Cura Fatma Gunseli Yasar Ciklacandir Günet Eroğlu Dept. of Biomedical Engineering Izmir Katip Celebi University Izmir TURKEY Dept. of Computer Engineering Izmir Katip Celebi University Izmir TURKEY Dept. of Computer Engineering Bahçeşehir University Istanbul Turkey

ISBN: (数字)9798331529819

ISBN: (纸本)9798331529826

Neuroscience has been significantly impacted by developments in computational techniques and machine learning algorithms, especially in the early diagnosis and classification of neurological illnesses. This study has been conducted to classify EEG data obtained from theta, alpha, beta1, beta2, and gamma bands to diagnose dyslexic and normal children. In addition to examining the individual classification performances of the data taken from these five bands, the classification success of the set created by combining the data from all bands has also been examined. The well-known models such as AlexNet, GoogleNet, and ResNet18 are compared with the revised version of ResNet18 developed in the study and the classification of handcrafted features with support vector machine (SVM). When the models’ performances are compared, it is seen that Revised ResNet18 gives results with the highest accuracy value in all bands except the Gamma band. Additionally, it has been observed that the classification success of handcrafted features is lower than the success of CNN-based models.

关键词： Support vector machines Pediatrics Sensitivity Accuracy filtering algorithms Brain modeling Dyslexia Electroencephalography Classification algorithms Overfitting

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