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检索条件"主题词=filtering algorithms"

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A Step-by-Step Multi-Stage Filter Design Method of an Active Three-Phase Three-Level Rectifier for Aircraft Application

A Step-by-Step Multi-Stage Filter Design Method of an Active...

引用

International Symposium on Power Electronics, Electrical Drives, Automation and Motion, SPEEDAM

作者： Robin Weiß Sebastian Rode Steffen Bernet Chair of Power Electronics Dresden University of Technology Dresden Germany

ISBN: (数字)9798350387599

ISBN: (纸本)9798350387605

The design of passive filters for rectifier topologies in modern aircraft is complicated by the variable frequency power supply and stringent regulatory requirements. This paper introduces a straightforward design approach that bypasses complex optimization algorithms, aiming to enhance power density. The referred method is applied to develop a passive, multi-stage filter for a bidirectional three-phase, three-level rectifier system.

关键词： Power system measurements Passive filters Power supplies Rectifiers Resonant frequency filtering algorithms Power electronics

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Design of an FPGA-based Image Defogging Algorithm Using Dark Channel Prior

Design of an FPGA-based Image Defogging Algorithm Using Dark...

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Electronic Information Engineering and Computer Science (EIECS), 2021 International Conference on

作者： Tingting Zhang Chengdu University of Information Technology School of Communication Engineering Chengdu Sichuan China

ISBN: (数字)9798331531409

ISBN: (纸本)9798331531416

In recent years, with the rapid advancement of digital image processing technology, image dehazing has become a focal point in both scientific research and practical applications. This paper presents a study on a dehazing algorithm based on the dark channel prior and its optimization for FPGA implementation. To improve image refinement and reduce algorithm complexity, the filter window size for calculating the dark channel is simplified to 3×3. When estimating the global atmospheric light intensity (A), the brightest pixel in the dark channel image is selected as the A value. Based on this, the transmission map is computed, and a guided filter is introduced to smooth the image. Finally, FPGA is utilized to accelerate the algorithm, and a low-pass filter is employed instead of the guided filter to further reduce complexity and enhance processing efficiency, meeting the real-time dehazing requirements for high-resolution images.

关键词： Computer science Digital images Low-pass filters Channel estimation filtering algorithms Information filters Real-time systems Complexity theory Field programmable gate arrays Optimization

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Diverse Image Processing Techniques for Machine Learning Methods

Diverse Image Processing Techniques for Machine Learning Met...

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IEEE International Conference on Intelligent Techniques in Control, Optimization and Signal Processing (INCOS)

作者： A. Bhagya S. Perumal Department of Computer Science Vels Institute of science Technology and Advanced Studies Chennai Tamil Nadu India

ISBN: (数字)9798350361186

ISBN: (纸本)9798350361193

Machine learning is a trending topic in the area of computer vision, which makes the machine able to learn about it without being expressly programmed using various algorithms. When a model is designed to predict future-based on historical data using machine learning algorithms, data is vital because high quality data is needed to run the model efficiently and to predict highly accurate results. Machine learning algorithms receive data in many forms, like audio (speech recognition), images (feature recognition), numeric data (like height and weight) etc. When it comes to computer vision, the machine learning algorithms must be able to understand the image data, and before the images are processed to the algorithms it should be pre-processed (cleaned and set to the desired format) using various image pre-processing techniques. This research paper presents various image processing techniques, literature reviews on various image processing techniques and image PSNR value after applying median filter, grayscale filter and box filters.

关键词： Machine learning algorithms Image processing Signal processing algorithms Speech recognition Machine learning Gray-scale filtering algorithms

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Dynamic Target Sensing for ISAC Systems in Clutter Environment

Dynamic Target Sensing for ISAC Systems in Clutter Environme...

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IEEE Conference on Wireless Communications and Networking

作者： Yucong Wang Hongliang Luo Feifei Gao Jianwei Zhao Huihui Wu Shaodan Ma Department of Automation BNRist Tsinghua University Beijing China College of Nuclear Engineering High-Tech Institute of Xi'an Xi'an China Department of Electrical and Computer Engineering University of Macau Macao S.A.R. China

ISBN: (数字)9798350303582

ISBN: (纸本)9798350303599

In this paper, we propose a practical integrated sensing and communications (ISAC) framework to sense dynamic targets from clutter environment while ensuring users communications quality. We design multiple communications beams that can communicate with users while one rotating sensing beam can scan entire space, and then we propose the supporting beam-forming design and power allocation strategies for such design. Unlike most existing ISAC studies that ignore the interference of static environmental clutter on target sensing, we construct a mixed sensing channel that includes both static environment and dynamic targets. When base station receives echo signals, we first provide a practical clutter filtering method to filter out static environmental clutter. Then dynamic target detection and angle estimation are realized through angle-Doppler spectrum estimation (ADSE) and joint detection over multiple subcarriers (MSJD), while distance and velocity estimation are realized through the extended subspace algorithm. Simulation results are provided to demonstrate the effectiveness of the proposed scheme.

关键词： Base stations filtering Heuristic algorithms Simulation Estimation Object detection filtering algorithms

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Improved Canny Edge Detection Algorithm

Improved Canny Edge Detection Algorithm

引用

International Symposium on Environmentally Conscious Design and Inverse Manufacturing (EcoDesign)

作者： Hongpeng Zhang Chang Liu Liangjie Feng Yang Yu School of Sciences Shanghai Institute of Technology Shanghai China

ISBN: (数字)9798350363043

ISBN: (纸本)9798350363050

This paper introduces an improved Canny edge detection algorithm. The algorithm replaces traditional Gaussian filtering with bilateral filtering, which better preserves edge structures and ensures more precise edge detection in detailed regions. Additionally, the algorithm employs adaptive histogram equalization to enhance the local contrast of the image. At the same time, the adaptive thresholding in the algorithm enhances the detection performance for edges of varying intensities, such as weak and strong edges, particularly in low-contrast areas. During non-maximum suppression, a neighborhood comparison of edge pixels is manually implemented based on gradient direction to ensure that only local maximum edges are retained, increasing the precision in processing gradient directions, particularly for slanted or subtle edges. Finally, the algorithm applies morphological techniques to refine edges. Experimental findings show that the enhanced algorithm boosts the accuracy of object edge detection from 0.717 to 0.750.

关键词： Histograms Accuracy filtering Image edge detection Heuristic algorithms Adaptive equalizers filtering algorithms Feature extraction Informatics Morphological operations

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Hybrid Real-time Recommendation System for Online E-Commerce

Hybrid Real-time Recommendation System for Online E-Commerce

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International Conference on Advances in Information Technology (ICAIT)

作者： Amar Kumar Amrutha Druthi Harshitha M Shashank Thillaiarasu N School of Computing and Information Technology REVA University Bengaluru India

ISBN: (数字)9798350383867

ISBN: (纸本)9798350383874

This project aims to enhance E-commerce recommendation systems by developing an Improved Hybrid Recommendation System. It overcomes the limitations of traditional methods by integrating collaborative and content-based filtering with advanced machine learning algorithms for improved accuracy, diversity, and adaptability to changing user preferences. The goal is to increase customer satisfaction, sales and build loyalty in a competitive e-commerce environment. The system utilizes a multi-mode algorithm, selecting the best approach based on existing data, and employs hybrid filtering combining collaborative and content-based techniques to provide effective product recommendations.

关键词： Machine learning algorithms Diversity reception Customer satisfaction Collaboration filtering algorithms Information filters Real-time systems Electronic commerce Information technology Recommender systems

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Comparative Study of CKF and UKF in Dimensionality Reduction Fast Transfer Alignment of Inertial Navigation Systems of Shipborne Equipment

Comparative Study of CKF and UKF in Dimensionality Reduction...

引用

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

作者： Yongjun Wang Jingshuo Xu Shaokang Ji Yantai Institute of Science and Technology Yantai Shandong China Qingdao Campus of Naval Aviation University Qingdao Shandong China

ISBN: (数字)9798350361445

ISBN: (纸本)9798350361452

Aiming at the problem of large azimuth between the ship-borne equipment coordinate system and the ship center coordinate system, a fast transfer alignment method is proposed. The nonlinear error equation of strapdown inertial navigation system (SINS) under the condition of large azimuth misalignment angle and ship deflection model are established. According to the requirements of rapidity and accuracy of transfer alignment, the state space model of reduced-dimension transfer alignment is constructed, and the fast transfer alignment method of speed plus attitude is designed. Using the high-precision inertial navigation information of ship-borne with strong anti-interference and autonomy as auxiliary information, and using CKF and UKF nonlinear filtering algorithms, the rapid transfer alignment of ship-borne inertial navigation under the condition of large azimuth misalignment angle is realized. The simulation results show that regardless of the level of sea conditions, CKF and UKF can achieve accurate estimation of attitude misalignment angle, which is the main alignment parameter of shipborne inertial navigation system, and the alignment accuracy can reaches the level of angular division.

关键词： Global navigation satellite system Accuracy Azimuth Simulation Sea measurements Inertial navigation filtering algorithms

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Long and Short-Term User Intent Learning for Sequence Recommendation

Long and Short-Term User Intent Learning for Sequence Recomm...

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International Joint Conference on Neural Networks (IJCNN)

作者： Zhiwei Zhang Fuzhen Sun Pengcheng Li Wenxuan Zhang Shaoqing Wang Tianhui Wu School of Computer Shandong University of Technology Zibo China Information Center(Emergency Services Center) Beijing Earthquake Agency Beijing China

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Personalized recommendation algorithms accurately mine users’ potential intentions by analyzing historical interaction data, deepening the user-item relationship and screening to filter complex information while effectively improving users’ experience and engagement. However, it is difficult to distinguish between embedded features and interaction relationships, and there is still the problem of lack of timeliness in intent representation. Aiming at the above problems, this paper proposes a sequence recommendation model that integrates users’ long and short-term intentions, which models users’ long and short-term intentions as potential factors over time at the fine-grained intention level of interaction, which accurately locates the users’ real intentions at a certain time. Firstly, a dual-layer gated recurrent network is designed to solve the sequential dependency problem in long-term sequences and to capture the changes in the user’s long-term intention through an intent evolution unit based on the attention mechanism. Secondly, an online meta-learning update strategy is optimized for real-time modeling of short-term intentions to take into account current temporal information and content relevance. Finally, the two types of intentions are adaptively fused to predict the interaction probability at the next time. Extensive experiments on three real-world datasets show that the LSI-Rec model significantly outperforms all baseline models on the recommendation task.

关键词： Metalearning Adaptation models Attention mechanisms Neural networks Logic gates filtering algorithms Information filters

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Algorithm research for stochastic dual control based on set member estimation

Algorithm research for stochastic dual control based on set ...

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Computer and Information Processing Technology (ISCIPT), International Symposium on

作者： Xiaoyan Zhang Yuxuan Xie Ziyan Shang Jiaoru Huang Suping Zhao Xiaohua Song School of Electronic Information Engineering Xi’an Technological University Xi’an China

ISBN: (数字)9798350388404

ISBN: (纸本)9798350388411

An ellipsoidal state bounding based set member estimation dual control method algorithm is proposed for the control problem under unknown but bounded noise. The algorithm designs a weighting factor in the time updating and the measurement updating phases of the setter estimation, respectively. The weighting parameter for the recursive phase of the measurement update is obtained by minimizing the upper bound of the Lyapunov function of the estimation error; a feedback control strategy is also incorporated to make the system operate towards the desired goal. The final results show that the designed controller ensures effective filtering of unknown but bounded noise and enables the system to achieve optimal control. Simulation studies further validate the effectiveness of the proposed method.

关键词： Weight measurement Uncertainty Upper bound Noise Measurement uncertainty Optimal control filtering algorithms

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Unravelling the Mysteries of Lung Cancer: Harnessing the Power of Deep Learning for Detection and Classification

Unravelling the Mysteries of Lung Cancer: Harnessing the Pow...

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Recent Advances in Electrical, Electronics, Ubiquitous Communication, and Computational Intelligence (RAEEUCCI), International Conference on

作者： M Dhayalini B. Revathi Alias Ponmozhi Electronics and Communication Engineering SET Dhanalakshmi Srinivasan University Trichy India

ISBN: (数字)9798350354539

ISBN: (纸本)9798350354546

Lung cancer is the leading cause of cancer- related death worldwide. Identifying lung nodules is essential in the early detection of lung cancer, which can progress to tumors. Computed tomography (CT) can help with the diagnosis of lung diseases. The primary goal is identifying malignant lung nodules and categorizing lung cancer as benign or malignant. Various image processing, biomarker-based, and machine-automated methods are used to detect lung cancer, but medical practitioners face challenges in achieving accuracy and early diagnosis. This work proposes a novel approach for early and accurate lung cancer diagnosis using the LeNet-5 algorithm. Initially, a median filter is used for preprocessing. Cancerous nodules in lung images were segmented using a hybrid fuzzy with a genetic algorithm (GA). The proposed LeNet-5 is implemented in MATLAB using the dataset obtained by the Lung Image Database Consortium and the Image Database Resource Initiative. Various performance parameters are compared and evaluated with existing algorithms and cutting-edge methods. The experimental outcomes demonstrate that the suggested algorithm has higher classification accuracy (99.2%) than other methods.

关键词： Image segmentation Image databases Computed tomography Lung cancer Lung filtering algorithms Sensitivity and specificity

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