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检索条件"主题词=Filtering algorithms"

共 10368 条记录，以下是1521-1530 订阅

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Hybrid Feature Selection Method Based Semi-Supervised for Transformer Fault Diagnosis

Hybrid Feature Selection Method Based Semi-Supervised for Tr...

引用

Energy Engineering and Power Systems (EEPS), International Conference on

作者： Xuemin Tan Jianglin Zhang Chao Guo Huimin Zhuang Xiaona Xie Yanxia Li The College of Automation Chengdu University of Information Technology Chengdu China Chengdu Power Supply Company State Grid Chengdu China

ISBN: (数字)9798350375138

ISBN: (纸本)9798350375145

The task of collecting labeled Dissolved Gas Analysis (DGA) data is challenging due to the time and cost involved in identifying transformer faults at substations. However, unlabeled DGA data is more readily available. To leverage the limited labeled DGA data and the abundant unlabeled data to enhance the transformer fault diagnosis rate, it is crucial to explore semi-supervised learning methods for DGA fault diagnosis that can address real-world challenges. This paper introduces an innovative Hybrid Feature Selection Method based Semi-supervised Learning (HFSM-SSL) that employs a filter-based method combined with wrapper-based in SSL to identify the most optimal DGA features. A XYZ strategy is proposed to augment the training dataset and select optical features in the filter-based process. The method is validated using the IEC TC10 dataset and is compared with standard and single optimization feature criterion diagnostic model. The findings demonstrate the effectiveness of the proposed algorithm and XYZ strategy in optimizing DGA features and its robustness in tackling classification problems with small DGA sample sizes.

关键词： Optical filters Training Integrated optics Semisupervised learning filtering algorithms Dissolved gas analysis Feature extraction Transformers Real-time systems IEC Standards

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Algorithmic approach for audio segmentation

Algorithmic approach for audio segmentation

引用

International Conference on System Theory, Control, and Computing (ICSTCC)

作者： Vasile-Silviu Sarmasanu Cristian Nicolae Butincu Vasile Ion Manta Andrei Stoleru Department of Computer Science Faculty of Automatic Control and Computer Engineering "Gheorghe Asachi" Technical University of Iasi Romania

ISBN: (数字)9798350364293

ISBN: (纸本)9798350364309

This paper presents an algorithmic approach for segmenting news broadcasts produced by television stations. The proposed approach uses advanced signal processing techniques to extract and classify audio segments from Romanian TV news broadcasts. By using derivative of 1-dimensional Gaussian filter and binary classification models, this paper aims to automatically identify and classify news segments into categories such as studio news, field news, commercials and music breaks. The primary objective of this paper is to develop a segmentation methodology optimized for reduced computational memory and quick processing. By leveraging efficient computational techniques, the news segmentation can be performed in a timely manner without compromising accuracy. This optimization is crucial for real-time or near-real-time applications within TV networks, facilitating tasks such as content monitoring and analysis.

关键词： TV Content management Accuracy Computational modeling Signal processing algorithms Signal processing filtering algorithms Real-time systems Classification algorithms Reliability

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Two Dimensional Sidelobes Reduction in SAR System

Two Dimensional Sidelobes Reduction in SAR System

引用

Electrical Engineering (ICEENG), 12th International Conference on

作者： Abdelaziz Ramadan Elshazly Ahmed Saleh Amein Fathy Mohamed Abdelkader Mohamed Safy Department of Radar Military Technical College Cairo Egypt Department of Computer Science October 6 University Giza Egypt Department of Computing and Information Technology Arab Academy for Science Technology and Maritime Transport Giza Egypt

ISBN: (数字)9798350343427

ISBN: (纸本)9798350343434

In this paper an optimized mismatched filter coefficients in both range and azimuth directions for SAR system are proposed, through using quadratic constrained quadratic program (QCQP) approach, that is convex optimization, to improve image quality, particularly with regard to main lobe width (MLW), signal noise ratio loss (SNRL), and peak sidelobe ratio (PSLR). Applying these mismatched filter coefficients in the modified chirp scaling algorithm (CSA) for both simulated and European Remote Sensing satellite (ERS) real data, shows approximately 15dB and 24dB improvement in PSLR compared with traditional CSA.

关键词： Image quality Satellites Azimuth Chirp Noise filtering algorithms Approximation algorithms

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Optimizing Medical Image Processing Performance through Chip Modeling

Optimizing Medical Image Processing Performance through Chip...

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Annual Information Technology, Electromechanical Engineering and Microelectronics Conference (IEMECON)

作者： Suvrojyoti Paul Subhankar Bhattacharjee Electronics and Communication Techno International New Town Plaksha University Kolkata India Electronics and Communication Techno International NewTown Kolkata India

ISBN: (数字)9798350387315

ISBN: (纸本)9798350387322

This paper presents a novel approach to optimizing the performance of medical image processing through SystemC chip modelling. Our unique contribution lies in the integration of hardware/software co-optimization technique tailored for medical imaging, which is distinct from conventional methods of either using software optimization or hardware acceleration techniques. We focus on three key image processing techniques: a Median filter for noise reduction, a Threshold filter for high-contrast conversion of grayscale or color pixels, and a Sobel filter for edge detection. These techniques, while crucial for identifying features in medical images, often come with a high computational cost. Our method tackles this problem. To demonstrate the effectiveness of our approach, we applied it to a group of images of a patient with cerebral cancer. Our results show that SystemC chip modeling can significantly improve the computational efficiency of medical image processing, with potential applications in various medical imaging technologies. After implementing the proposed hardware model, there was an improvement of nearly 5.5 times compared to the software optimizations, and a 20-fold enhancement over the initial default implementation.

关键词： filtering Computational modeling Software algorithms filtering algorithms Software Computational efficiency Biomedical image processing Microwave filters Optimization Biomedical imaging

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Real-valued Beamspace Direct Position Determination for Multi-Station Systems

Real-valued Beamspace Direct Position Determination for Mult...

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6th International Conference on Intelligent Computing and Signal Processing (ICSP)

作者： Bo Wang Ziheng Zhao Qi Liu Rui Guo School of Electronics and Communication Engineering Sun Yat-sen University Shenzhen China

ISBN: (数字)9798350376548

ISBN: (纸本)9798350376555

The direct position determination method has demonstrated superior performance over conventional two-step methods in low signal-to-noise ratio scenarios, as it utilizes measurements from all base stations without the need for intermediate parameter estimation. However, for large-scale multi-station systems, this technology requires significant communication and computational overheads. In this paper, we propose a real-valued beamspace direct position determination method, which involves beamspace design, real-valued processing and direct localization computation. Unlike the traditional DFT beamspace filter, the beamspace design is formulated as an optimization problem, leading to lower performance loss. By performing a unitary transformation on the received signals, the algorithm is converted from the complex domain to the real domain, further reducing computational complexity. Simulation results demonstrate that the algorithm significantly reduces computational and communication overheads while maintaining excellent localization performance.

关键词： Location awareness Parameter estimation Simulation Signal processing algorithms Position measurement filtering algorithms Computational complexity Optimization Signal resolution Signal to noise ratio

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Simultaneous input and state estimation for systems with arbitrary inherent delay

Simultaneous input and state estimation for systems with arb...

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IEEE Conference on Decision and Control

作者： Grigorios Gakis Malcolm C. Smith Department of Engineering University of Cambridge England UK

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

The purpose of this paper is to present a filtering algorithm for simultaneous input and state estimation for linear discrete-time systems of any inherent delay. It generalises previous work which was restricted to systems with an inherent delay of less than or equal to one. The algorithm includes the Kalman filter which is itself a special case of a system with an inherent delay of zero. The approach uses a standard characterisation of a system’s inherent delay in terms of its rank indices. Two judiciously chosen rank decompositions of a Toeplitz matrix of the system’s Markov parameters are used to develop the algorithm. The filter is illustrated on a simple two-mass system with an inherent delay of two.

关键词： Discrete-time systems filtering algorithms Delays Matrix decomposition Kalman filters State estimation Standards

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Kernel Correlation Filter Algorithm and Its Research in Small Target and Occlusion Fields

Kernel Correlation Filter Algorithm and Its Research in Smal...

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Intelligent Robotics and Automatic Control (IRAC), International Conference on

作者： Wenhu Li Yanfei Tang Youling Xiong Fei Wang Computer and Network College of Anhui Postal and Telecommunications Vocational and Technical College Hefei China School of Financial Technology Anhui Vocational and Technical College of Commerce Wuhu China

ISBN: (数字)9798350389807

ISBN: (纸本)9798350389814

This paper focuses on the improvement of kernel filtering algorithms and their applications, particularly on enhancing the accuracy of target recognition and tracking in modern intelligent environmental monitoring. The Kernel Correlation Filter (KCF) algorithm, due to its efficiency, high precision, and strong robustness, holds significant potential for application in surveillance environments. However, the performance of the KCF algorithm is limited in complex scenarios such as occlusion, scale changes, similar targets, and rapid *** address these issues, this paper proposes two improved KCF algorithms. Firstly, a scale pool algorithm is introduced, which enhances the algorithm's adaptability to target scale changes by performing multi-scale feature extraction and matching, thereby improving tracking accuracy, efficiency, and speed. Experiments demonstrate that the tracking accuracy of the improved algorithm is significantly enhanced on the OTB50 and OTB100 datasets. In experiments using a self-constructed dataset, the success rates for feature extraction, scale changes, and sampling rates were improved by 40%, 13.6%, and 29.76%, ***, to address the occlusion problem, an improved joint tracking algorithm combining the modified KCF with ByteTrack is proposed. The high-quality detection results of the improved KCF are utilized as input for ByteTrack, which optimizes the handling of occluded objects through its multiple matching strategies. The joint algorithm exhibits excellent performance on the OTB50 and OTB100 datasets. In the self-constructed dataset, the success rate for handling occlusion scenarios is improved by 50% compared to the original KCF, effectively solving issues such as target template updating, feature changes, and target disappearance.

关键词： Target tracking Accuracy Correlation Target recognition Surveillance filtering algorithms Feature extraction Robustness Kernel Robots

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An Online Evaluation Based Extended-State Kalman Filter Approach to Navigation Via Signal of Opportunity

An Online Evaluation Based Extended-State Kalman Filter Appr...

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Data Driven Control and Learning Systems (DDCLS)

作者： Junyuan Liu Xuanwen Chen Sen Chen Wenyan Bai Yinghui Wang Zhiliang Zhao Airborne Avionics Flight Test Institute Chinese Flight Test Establishment Xi'an China School of Mathematics and Statistics Shaanxi Normal University Xi'an China Beijing Aerospace Automatic Control Institute Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing China School of Electrical and Control Engineering North Central University Taiyuan China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

This paper studies the problem of multi-source opportunistic signal navigation of aircraft. Firstly, the paper provides the mathematical models for five types of opportunistic signals. Furthermore, the online evaluation algorithm based on T-test is proposed for seeking the biased opportunistic signals. By disposing of the opportunistic signals causing intolerant location error, an estimated location position is obtained by trusty opportunistic signals. Finally, to handle the unknown part of flight acceleration caused by external disturbances, the extended-state Kalman filter is constructed to promote the locating accuracy. The simulation results show the effectiveness of the proposed method.

关键词： Learning systems filtering Heuristic algorithms Simulation filtering algorithms Control systems Mathematical models

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Aggregation Algorithm in Text Translation Systems

Aggregation Algorithm in Text Translation Systems

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Data Science and Information System (ICDSIS), IEEE International Conference on

作者： Yang Li Chengdu Neusoft University Chengdu China

ISBN: (数字)9798350381665

ISBN: (纸本)9798350381672

In order to solve the problem of time-consuming and inaccurate translation in current translation systems, this paper constructs a text translation system based on the K-means clustering algorithm under the aggregation algorithm. This article takes the shared corpus of the Information Retrieval Research Office of Harbin Institute of Technology as an example to compare the translation time and accuracy of different sentence lengths in four different genres. The research results of this article found that the translation system based on K-means algorithm has the best performance, and its translation time is relatively short. The translation accuracy can reach over $\mathbf{9 5 \%}$, far higher than traditional translation systems. This indicates that aggregation algorithms can play an important role in text translation systems.

关键词： Accuracy Costs Clustering algorithms filtering algorithms Search engines Data science Information filters

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Research on Weak Signal Processing Methods for Electrical Imaging Logging Tools

Research on Weak Signal Processing Methods for Electrical Im...

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Semiconductor and Electronic Technology (ISSET), International Symposium on

作者： Fenfen Yang Yi Gao School of Electronic Engineering Xi’ an Shiyou University Xi'an China

ISBN: (数字)9798350390285

ISBN: (纸本)9798350390292

Using the actual formation resistivity and porosity spectrum information, the electroimaging tool can quickly estimate the oil content of complex reservoirs, and can recognize the sedimentary structure and micro-cracks in tight oil and gas reservoirs by improving the measurement accuracy of the instrument. For electrical imaging logging, improving the detection accuracy of weak signals is a necessary condition for enhancing the quality of logging data, improving imaging resolution, and making imaging clearer. In response to the problem that current processing algorithms for electrical imaging logging signals cannot guarantee complete signal information while denoising, this paper establishes a logging noise signal analysis model based on the characteristics of logging signals, and uses wavelet transform and three adaptive LMS filtering algorithms to process the model. Simulation experiments on MATLAB show that the maximum mean square error of the adaptive LMS algorithm is greatly reduced than that of the wavelet method, which shows that the method has better filtering performance. Among the three adaptive LMS algorithms, the $1/2\text{LMS}$ algorithm has the fastest running speed and the lowest MSE value, making it the most suitable for measuring weak signals underground.

关键词： Wavelet transforms Analytical models Adaptation models Oils Noise reduction Signal processing algorithms Imaging filtering algorithms Reservoirs Mathematical models

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