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检索条件"主题词=Filtering algorithms"

共 10367 条记录，以下是941-950 订阅

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Sliding Mode Based Model Predictive Controller for Single-Phase Multilevel T-type Inverters with LCL Filter

Sliding Mode Based Model Predictive Controller for Single-Ph...

引用

IEEE International Conference on Automatica (ICA-ACCA)

作者： Mokhtar Aly Eltaib Abdeen D. Ibrahim Fernanda Carnielutti Margarita Norambuena Mohamed Abdelrahem Ahmed Elsanabary José Rodriguez Facultad de Ingeniería Arquitectura y Diseño Universidad San Sebastián Bellavista 7 Santiago Chile Electrical Engineering Department High Institute for Engineering and Technology in Sohag Sohag Egypt Federal University of Santa Maria (UFSM) Santa Maria Brazil Electrical Engineering department Universidad Tecnica Federico Santa Maria Valparaiso Chile Dept. of Elec. Eng. Faculty of Eng. Assiut University Assiut Egypt Department of Electrical Engineering Port Said University Port Fouad Egypt

ISBN: (数字)9798350378115

ISBN: (纸本)9798350378122

This paper presents an improved sliding mode-based finite control set model predictive controller for grid-tied single-phase multilevel inverter systems with an LCL filter. The proposed controller employs the inherent robustness of sliding mode control (SMC) with the fast dynamic response of the FCS-MPC method for controlling the complex behavior of LCL filter-based grid-tied inverter systems. The LCL-based grid-tied multilevel inverters necessitate the control of inverter side and grid side currents in addition to the grid filter capacitor voltage and DC-link capacitors voltage control/balance. Incorporating FCS-MPC with SMC eliminates the chattering effects in the traditional SMC algorithms. Moreover, incorporating SMC with FCS-MPC enables more robust and stable control performance compared to the conventional FCS-MPC method. The proposed method eliminates the need for weighting factors for DC-link capacitor voltage balance by properly selecting redundant voltage vectors. Simulation results are provided to validate the proposed SMC-based FCS-MPC controller with different active and reactive power injections to the grid.

关键词： Uncertainty Simulation Capacitors Predictive models filtering algorithms Multilevel inverters Robustness Vectors Voltage control Sliding mode control

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Filtered Tensor Ring-Based Algorithm for Low-Rank Image Completion

Filtered Tensor Ring-Based Algorithm for Low-Rank Image Comp...

引用

International Multidisciplinary Conference on Computer and Energy Science (SpliTech)

作者： Rafał Zdunek Faculty of Electronics Photonics and Microsystems Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (数字)9789532901351

ISBN: (纸本)9798350390797

The issue of image completion has attracted increasing interest in many areas of science and engineering, including smart and information technologies. In this study, we propose a new computational method for a low-rank image completion problem, where an incomplete image has a large number of uniformly distributed missing pixels or a regular missing structure, e.g. a grid. The proposed method combines a low-rank approximation, enforced by the tensor ring decomposition model, with in-line low-pass filtration. The numerical experiments with strongly incomplete images demonstrate high efficiently of the proposed method.

关键词： Location awareness Tensors Image resolution Filtration Computational modeling filtering algorithms Approximation algorithms

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Near-End Listening Enhancement Using a Noise-Robust Linear Time-Invariant Filter

Near-End Listening Enhancement Using a Noise-Robust Linear T...

引用

International Workshop on Acoustic Signal Enhancement (IWAENC)

作者： Filippo Villani Wai-Yip Chan Zheng-Hua Tan Jan Østergaard Jesper Jensen Department of Electronic Systems Aalborg University Aalborg Denmark Department of Electrical and Computer Engineering Queen’s University Kingston Canada Oticon A/S Smørum Denmark

ISBN: (数字)9798350361858

ISBN: (纸本)9798350361865

In environments with competing sound sources, speech intelligibility can be significantly compromised. This paper addresses the near-end listening enhancement (NELE) problem, i.e., the problem of processing an available clean speech signal in order to maximize its intelligibility when it is subsequently presented to a human listener in an adverse acoustic situation. We propose a time-invariant and low-complexity NELE algorithm that maximizes an approximation of the Speech Intelligibility Index by redistributing speech energy across frequency bands. Unlike existing algorithms, the proposed algorithm incorporates a mechanism that allows it to distinguish between temporally fluctuating and non-fluctuating noise maskers by using only long-term speech and noise statistics. Simulation results show that the proposed method outperforms baseline algorithms, whether time-invariant or time-varying, in a wide range of noise conditions.

关键词： Time-frequency analysis Working environment noise Simulation Noise Nonlinear filters Speech enhancement filtering algorithms Approximation algorithms Acoustics Indexes

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Research on High Precision Distance Measurement of Femtosecond Laser Based on Discrete Kalman Filter

Research on High Precision Distance Measurement of Femtoseco...

引用

Advanced algorithms and Control Engineering (ICAACE), International Conference on

作者： Zeming Zhang Tianliang Jiao Sheng Zhang Yuanqin Xia The National Key Laboratory of Science and Technology on Tunable Laser Harbin Institute of Technology Harbin China School of Mechatronics Engineering Harbin Institute of Technology Harbin China School of Physics Harbin Institute of Technology Harbin China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

The development of dual femtosecond laser absolute distance measurement technology, based on the time-of-flight method, presents a novel approach for applications requiring extensive range, precision, resolution, and update rate. However, the introduction of Gaussian white noise during the measurement process may lead to a reduction in distance measurement accuracy. This study proposes a method employing discrete Kalman filtering technology to enhance the precision of dual femtosecond laser absolute ranging by obtaining real-time estimation values of velocity information for dynamic targets. When the target is in motion, the Kalman filtering technique can concurrently ascertain the estimated velocity information of the moving target. The standard deviation of the estimated velocity for a uniformly moving target in a stable state is approximately $4\ \mu \mathrm{m}\ \mathrm{s}^{-1}$ . Additionally, when the target undergoes sinusoidal vibration, the Kalman filtering technique effectively tracks the measurement results and significantly enhances measurement accuracy.

关键词： Vibrations filtering Laser noise Measurement by laser beam Vibration measurement filtering algorithms Distance measurement

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Towards a Mixed Learning Strategy for Discovering New Gene Signatures in Breast Cancer Prognosis

Towards a Mixed Learning Strategy for Discovering New Gene S...

引用

IEEE Biennial Congress of Argentina (ARGENCON)

作者： Cristhian Cola-Pilicita Mateo Martínez-Mejía Eduardo Alba Yovani Marrero-Ponce Noel Pérez-Pérez Colegio de Ciencias e Ingenierías Universidad San Francisco de Quito USFQ Quito Ecuador Colegio de Ciencias de la Salud Universidad San Francisco de Quito USFQ Quito Ecuador

ISBN: (数字)9798350365931

ISBN: (纸本)9798350365948

This work focuses on developing a mixed-learning method that combines a filter-based metaheuristic searcher with a shallow learning classifier to reduce the feature space while maximizing the breast cancer prognosis classification. The searcher used a genetic algorithm together with the average symmetrical uncertainty (aSU) and ReliefF (aReliefF) filter functions. This modification allowed us to measure the relevance per capita of a group of features (genes). The proposed method was validated on a data set with 396 instances. The most effective classification scheme emerged from the random forest model, utilizing 60 tree predictors and employing the aReliefF objective function. This configuration achieved an average area under the receiver operating characteristic curve (AUC) score of 0.854 and 0.874 for the training and test stages, respectively. Thus, this classification scheme is the best breast cancer prognosis classification strategy. In addition, we identified a set of master genes through the intersection of both objective functions regarding feature relevance. Nevertheless, evaluating this subset in the test set using the top-performing classification scheme yielded a comparatively lower performance (AUC=0.829), underscoring the necessity for additional genes to maximize classification effectiveness.

关键词： Training Uncertainty Receivers filtering algorithms Predictive models Linear programming Breast cancer Object recognition Prognostics and health management Random forests

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Optimizing Resume Screening with Machine Learning: An NLP Approach

Optimizing Resume Screening with Machine Learning: An NLP Ap...

引用

International Conference on Computational Intelligence and Networks (CINE)

作者： Amiya Ranjan Panda Rohan Kumar Ahona Ghosh Lucky Das Manoj Kumar Mishra Mahendra Kumar Gourisaria School of Computer Engineering KIIT Deemed to be University Bhubaneswar Odisha

ISBN: (数字)9798331516796

ISBN: (纸本)9798331516802

In the digital hiring landscape, managers face challenges in resume screening due to time constraints, biases, and high application volumes. This study takes a closer look at how natural language processing and machine learning are being used to speed things up for resume screening. By diving into lots of research, this study showcases how promising natural language processing systems can be. Details about the data set have been elaborated in the methodology part, like how the data is created and all different machine learning models tried out for classifying resumes. Using the Bag-of-Words method, the Gaussian Naive Bayes model we achieved high accuracy rates-almost 99.5 %. These findings indicate that NLP algorithms can effectively filter resumes, aiding recruiters in identifying top candidates efficiently while minimizing biases and saving time and costs. Ultimately, we highlight the potential of these systems to enhance the hiring process.

关键词： Machine learning algorithms Accuracy Computational modeling Resumes Predictive models filtering algorithms Natural language processing Data models Bayes methods Time factors

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Robustness Evaluation of Localization Techniques for Autonomous Racing

Robustness Evaluation of Localization Techniques for Autonom...

引用

Design, Automation and Test in Europe Conference and Exhibition

作者： Tian Yi Lim Edoardo Ghignone Nicolas Baumann Michele Magno Center for Project-Based Learning ETH Zürich

ISBN: (数字)9783981926385

ISBN: (纸本)9798350348606

This work introduces SynPF, an MCL-based algorithm tailored for high-speed racing environments. Benchmarked against Cartographer, a state-of-the-art pose-graph SLAM algorithm, SynPF leverages synergies from previous particle-filtering methods and synthesizes them for the high-performance racing do-main. Our extensive in-field evaluations reveal that while Cartogra-pher excels under nominal conditions, it struggles when subjected to wheel-slip-a common phenomenon in a racing scenario due to varying grip levels and aggressive driving behaviour. Conversely, SynPF demonstrates robustness in these challenging conditions and a low-latency computation time of 1.25 ms on on-board computers without a GPU. Using the FITENTH platform, a 1:10 scaled autonomous racing vehicle, this work not only highlights the vulnerabilities of existing algorithms in high-speed scenarios, tested up until $7.6 \text{ms}^{-1}$ , but also emphasizes the potential of SynP F as a viable alternative, especially in deteriorating odometry conditions.

关键词： Location awareness Computers Simultaneous localization and mapping Computational modeling Graphics processing units filtering algorithms Benchmark testing

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L-Dissipativity of Hyperstable Repetitive Control Systems

L-Dissipativity of Hyperstable Repetitive Control Systems

引用

International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： E. A. Shelenok Higher School of Cybernetics and Digital Technologies Pacific National University Khabarovsk Russia

ISBN: (数字)9798350395013

ISBN: (纸本)9798350395020

In this research author proposed the method for constructing the hyperstable repetitive control systems for nonstrictly minimally phase linear dynamic plant which are subjects to the constant action of external periodic perturbations. To build a stable control system, the V.M. Popov's hyperstability criterion is used. Compensation of external disturbances and also adaptation to a periodic command action is carried out by the generator for periodic signals in the forward channel of the system. Ldissipativity of a hyperstable system is provided with the help of the high-speed dynamic correction filter which introduce into the main control loop. Main feature of the proposed solution is to provide the desired properties of the control system by bringing the relative degree of the control plant to a single value. At the same time, the operability of the system under consideration in the presence of a structural disturbance is ensured by fulfilling special conditions that impose requirements on the value of the time constant of the correction filter. The results of present research can be used in the development of hyperstable repetitive control systems for different complex classes of dynamic plants. For example, when the mathematical models of plant contain non-linear and/or non-stationary characteristics. In this case, the main problem will be to synthesize the dynamic feedback algorithms.

关键词： Heuristic algorithms Perturbation methods Design methodology filtering algorithms Industrial engineering Control systems Mathematical models

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An Edge Detection Algorithm of Noisy Image Based on OTSU Adaptive Threshold Segmentation

An Edge Detection Algorithm of Noisy Image Based on OTSU Ada...

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Image Processing, Electronics and Computers (IPEC), Asia-Pacific Conference on

作者： Jingjing Wang Shiming Lin Kang Zhang School of Information Engineering Changji College Changji China School of Informatics (National Demonstrative Software School) Xiamen University Xiamen China

ISBN: (数字)9798350374407

ISBN: (纸本)9798350374414

In order to solve the problem that the traditional edge detection algorithm is not effective in the edge detection of noisy image, this paper proposes an adaptive threshold OTSU based edge detection algorithm of noisy image. The algorithm takes into account the selection of filtering methods and thresholds, replacing the Gaussian filter used in the traditional Canny algorithm with an improved median filter. Secondly, the maximum inter-class variance OTSU is used to self-adapt the segmentation threshold. Firstly, the improved median filter algorithm removes part of the particle noise and preserves the edge to the maximum extent. Then the DoG operator is used to extract the edge information of the image, and finally the adaptive threshold value is calculated to the final binary edge detection image. Experimental results show that compared with traditional algorithms, the proposed algorithm has higher edge detection accuracy and better anti-noise performance.

关键词： Computers Image segmentation Accuracy Image edge detection Noise Dogs filtering algorithms Information filters Noise measurement Data mining

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Estimation of Road Adhesion Coefficient Using Strong Tracking CKF with M -Estimation Theory

Estimation of Road Adhesion Coefficient Using Strong Trackin...

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Conference on Vehicle Control and Intelligence (CVCI)

作者： Shuo Bai Zhaoyu Qiu Lilin Shen Weihua Wang Xiaolong Cheng Guodong Yin School of Mechanical Engineering Southeast University Nanjing China School of Cyberspace Security Southeast University Nanjing China

ISBN: (数字)9798331504892

ISBN: (纸本)9798331504908

Real-time acquisition of road adhesion coefficient (RAC) makes great sense to advanced driver assistance system. RAC cannot be obtained straightly from vehicular sensors considering the limited cost. Few studies concentrate on the estimation algorithms under model mismatch and unknown non-Gaussian noise. To deal with the challenge, a strong tracking cubature Kalman filtering on the basis of M- Estimation theory (STCKF-ME) has been proposed. Strong tracking filtering is employed to refresh the filter matrix. M- Estimation theory is adopted to guarantee the estimation precision under unknown non-Gaussian observation noise. Results demonstrate that STCKF-ME has an outstanding performance for RAC estimation when compared with CKF and STCKF. Moreover, STCKF-ME shows strong anti- disturbance ability to different driving cycles and road surface.

关键词： Adhesives filtering Roads Noise Estimation theory filtering algorithms filtering theory Stability analysis Sensors Kalman filters

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