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检索条件"主题词=Filtering algorithms"

共 10367 条记录，以下是1101-1110 订阅

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A Modelling Method for Grid Filter Topology Optimization

A Modelling Method for Grid Filter Topology Optimization

引用

IEEE Energy Conversion Congress and Exposition, ECCE

作者： Tim Lackie Gopal Mondal Teng Long Sebastian Nielebock Department of Engineering University of Cambridge Cambridge United Kingdom Department of Corporate Technology (CT) Siemens Corporate Research Erlangen Germany

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

Use of wide bandgap power semiconductors for grid connected active rectifiers shows great potential for highly efficient and power dense systems. To fully unlock these benefits, ideal filter design methods should: target the whole conducted emissions frequency range, be filter topology agnostic, and be suitable for use with optimisation methods. In this paper a novel filter modelling method is described, which uses a top-level filter topology with the ability to robustly replace some components with short-circuits or open-circuits to produce many smaller effective topologies as needed. Analysis methods to calculate critical parameters of the filter, including its effective input inductance are described, all of which are independent of the effective filter topology. The calculated parameters are used to predict the currents and therefore losses throughout the filter, using a time domain piecewise linear model for the ripple currents to predict switching and conduction losses in the converter. The emissions of the filter are also predicted in the modelling. To use the novel model for optimal filter design, an objective function is described, which outputs the system losses and filter volume as its objectives, using the predicted conducted emissions as a constraint. To verify that the model is accurate, measurements of the filter input impedance, converter current, system power losses and predicted emissions are compared to the corresponding predicted values from the model. The accuracy of the model is good, with the maximum error in the system losses being 5.0 %. With the model’s accuracy verified, the objective function is used within a genetic algorithm, demonstrating the models suitability for optimisation.

关键词： Solid modeling Accuracy Computational modeling Electromagnetic interference Optimization methods Predictive models filtering algorithms Linear programming Loss measurement Topology

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Research on Multiple Projection Algorithm Based on Relaxation-Tightening Optimization Strategy

Research on Multiple Projection Algorithm Based on Relaxatio...

引用

Artificial Intelligence, Networking and Information Technology (AINIT), International Seminar on

作者： Xi Zhao Weihao Yu Sheng Lu Tianyu Zhou Xiang Chen Congying Deng Chongqing University of Posts and telecommunications Chongqing People's China

ISBN: (数字)9798350385557

ISBN: (纸本)9798350385564

A large number of researchers use topology optimization to design cooling channels, and in order to ensure that the optimal solution of the distribution structure of cooling channels can be better obtained during topology optimization, it is necessary to introduce filtering algorithms and projection algorithms to filter and project the density values. This method enables the density values after processing to be concentrated on 0 and 1, and avoids cells with density values between 0 and 1. In order to achieve this goal, the common projection method is improved. Using two projection formulas with the same algorithms but different boundary thresholds, the density obtained by the projection method with the larger boundary threshold is provided to the volume constraint function, and the density obtained by the projection method with the smaller boundary threshold is provided to the optimization objective function. A relaxation-tightening optimization strategy is proposed in order to obtain the global optimal solution. Experimental results show that the improved projection method and relaxation tightening optimization strategy can effectively improve the computational efficiency and optimization efficiency of the cooling channel topology optimization algorithm.

关键词： Seminars Cooling Network topology Optimization methods filtering algorithms Linear programming Topology

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A filtering Method for SIFT based Palm Vein Recognition

A Filtering Method for SIFT based Palm Vein Recognition

引用

Proceedings of the Digital Image Computing: Technqiues and Applications (DICTA)

A key issue with palm vein images is that slight movements of fingers and the thumb or changes in the hand pose can stretch the skin in different areas and alter the vein patterns. This can produce palm vein images with an infinite number of variations for a given subject. This paper presents a novel filtering method for SIFT based feature matching referred to as the Median Distance (MMD) Filter, which checks the difference of keypoint coordinates and calculates the mean and the median in each direction, and uses a set of rules to determine the correct matches. Our experiments conducted with the 850nm subset of the CASIA dataset show that the MMD filter can detect and filter false positives that were not detected by other filtering methods. Comparison against existing SIFT based palm vein recognition systems demonstrates that the proposed MMD filter produces excellent performance with lower EER values.

关键词： Matched filters Image recognition Sensitivity Machine learning algorithms filtering Veins Thumb filtering algorithms Skin Recording

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Research on Maneuvering Target Tracking Algorithm Based on an Improved Particle Filter Algorithm

Research on Maneuvering Target Tracking Algorithm Based on a...

引用

IEEE/OES China Ocean Acoustics (COA)

作者： Li Baomin Pan Xiefan Shanghai MarineElectronic Equipment Research Institute Shanghai China

ISBN: (数字)9798350340297

ISBN: (纸本)9798350340303

In tracking scenarios of maneuvering targets, the model probability impacts the accuracy of the traditional interacting multiple model (IMM) algorithm based on a particle filter (PF), which leads to tracking errors. In this study, a PF algorithm based on multiple hypothesis model (MHM) is proposed. The maneuvering target tracking algorithm based on MHM-PF adopts the idea of a multi-hypothetical model and obtains the most likely motion model at each moment by comprehensively scoring the possible motion state model of the target at each moment, which can more accurately realize the maneuvering target tracking. Compared with the Kalman filter algorithm, which is limited by linear and Gaussian conditions, PF can make the algorithm suitable for nonlinear and non-Gaussian conditions. The simulation results reveal that the proposed algorithm has better tracking performance in maneuvering target tracking scenarios.

关键词： Matched filters Analytical models Target tracking Accuracy Simulation Oceans filtering algorithms Particle filters Acoustics Kalman filters

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Artificial Intelligence based Healthcare Knowledge Structure for Automatic Medical Report Generation

Artificial Intelligence based Healthcare Knowledge Structure...

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International Conference on Contemporary Computing and Informatics (IC3I)

作者： Pramod Kumar Faisal Yousef Alghayadh Vinay Prasad Tamta Dr Monika Anand Mukesh Soni Jitendra Kumar Chaudhary Jhajjar - Bahadurgarh Road Kablana Ganga Institute of Technology and Management Bhadana Haryana India Computer Science and Information Systems Department College of Applied Sciences AlMaarefa University Riyadh Saudi Arabia Department of Information Technology HNB Garhwal University (Central) Srinagar Uttarakhand India Department CSE Chandigarh University Mohali Punjab India Division of Research and Development Lovely Professional University Phagwara Punjab India School of Computing Graphic Era Hill University Bhimtal Campus Uttarakhand India

ISBN: (数字)9798350350067

ISBN: (纸本)9798350350074

Automatic medical report production is a key text summarization application. Traditional text summarizing systems cannot completely interpret and use medical texts’ complicated vocabulary due to the disparities between medical consultation data and general domain data. The crucial knowledge in medical consultations has not been successfully harnessed. Traditional text summary algorithms cannot automatically identify, and filter key information based on medical reports’ structure and generate structured text. An AI-based knowledge-assisted structured medical report creation solution addresses these difficulties. This method uses entity-guided previous domain knowledge and structure-guided task decoupling to fully utilize medical consultation data and medical report structure. The suggested strategy improves ROUGE scores by 2% to 3% compared to similar methods, resulting in more accurate medical reports, according to IMCS21 dataset experiments.

关键词： Vocabulary Computational modeling Text summarization Medical services Production Computer architecture filtering algorithms Information filters Informatics Standards

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Kernel-Based Target Tracking Using Bearing-Only Measurements

Kernel-Based Target Tracking Using Bearing-Only Measurements

引用

International Conference on Control, Automation and Information Sciences (ICCAIS)

作者： Yuanyuan Ji Linfeng Xu Shunyi Luo Peijie Yang School of Automation Northwestern Poly technical University Xi'an China

ISBN: (数字)9798331542047

ISBN: (纸本)9798331542054

Passive infrared sensors serve as the primary sensing device for air-to-air missiles. However, the bearing-only measurements they provide often lead to challenges related to low observability and high nonlinearity, complicating the acquisition of complete state information. Furthermore, the targets being tracked frequently exhibit complex motion patterns due to aggressive maneuvers during evasion or combat, making it difficult to determine their motion models a priori. To tackle the tracking problem for the highly maneuvering targets in such complex scenarios, this paper presents a self-learning method based on data-driven Gaussian processes regression, which can learn nonlinear relationships from the data. In particular, a multi-kernel approach is employed to address the limitations of a single kernel, allowing for a more comprehensive capture of the diverse characteristics of the data and enhancing overall tracking performance. The effectiveness of the proposed multi-kernel Gaussian Process regression based tracking within the interacting multi-model framework is validated through simulations.

关键词： Adaptation models Target tracking Trajectory tracking Simulation Process control Gaussian processes Switches filtering algorithms Trajectory Kernel

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Construction of Oral English Learning Model based on Multi-Head Attention with Long Short-Term Memory

Construction of Oral English Learning Model based on Multi-H...

引用

Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： Haie Jia Tibet Agricultural and Animal Husbandry College Nyingchi China

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

One of the significant problems in the College English education of Chinese students is that traditional class teaching materials are not well supported by sufficient English learning resources, with key language points nowhere well covered systematically. The Multi-Head Attention with Long Short-Term Memory (MHA-LSTM) is proposed in this research for the construction of Oral English Learning. The MHA enable to process different segments of input sequence at similar time to extract linguistic properties. The MHA is integrated into LSTM which captures long-term dependencies including retention key phrases and grammar rules in long-sequences. The median filter is a nonlinear statistical filter which is used as preprocessing for system performance of signals and images by elimination of noise. The Mel Frequency Cepstral Coefficients (MFCC) is used as feature extraction which track dynamic characteristics of speech like positive and negative changes which are needed to recognize the prosodic features of language where the intonation and tones which are important in learning and using spoken language. The MHA-LSTM achieves 92.5% accuracy, 89.7% sensitivity, 88.3% precision and 89.1% f-measure which is better than existing algorithm.

关键词： Sensitivity Noise Education Speech recognition filtering algorithms Feature extraction Grammar Data mining Mel frequency cepstral coefficient Long short term memory

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Imitation Learning from Suboptimal Demonstrations via Discriminator Weighting

Imitation Learning from Suboptimal Demonstrations via Discri...

引用

Chinese Control and Decision Conference, CCDC

作者： Liuyuan He Guoyu Zuo Jiangeng Li Shuangyue Yu Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

Imitation learning algorithms for robotics applications require sufficient optimal data to learn well-performing strategies. State-of-the-art approaches utilize pre-labeled data or interaction with the environment to filter suboptimal data, which is time-consuming and laborious in reality. In this paper, we propose a new approach that avoids manual labeling or environment interaction. We design an additional discriminator for the behavioral cloning approach to distinguish the optimal and suboptimal data in order to influence policy learning and avoid suboptimal behaviors. Within this framework, we design a new imitation learning algorithm that utilizes the output of the discriminator as weights to learn efficiently on datasets containing suboptimal data. We evaluate the performance of the proposed method in four environments and compare it with three benchmark methods. The results illustrate that our method has better performance when dealing with datasets containing suboptimal data. The method we proposed can distinguish data with higher values in the dataset and enable the agent to learn high-performance policy from imperfect demonstrations or a small amount of data.

关键词： Imitation learning Cloning Manuals filtering algorithms Benchmark testing Labeling Robots

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A Low-Power ABR Characteristic Waveform Automatic Detection Algorithm Design and FPGA Implementation

A Low-Power ABR Characteristic Waveform Automatic Detection ...

引用

International Conference on Microelectronics, ICM

作者： Fei You Manlin Lu Yahao Song Jingwen Zhang Sichao Liang Wenjing Chen Milin Zhang Xin Li Department of Electronic Engineering Tsinghua University Beijing China Beijing Tsinghua Changgung Hospital Beijing China

ISBN: (数字)9798350379396

ISBN: (纸本)9798350379402

Portable, low-power ABR characteristic waveform automatic identification devices have broad application prospects in clinical and scientific research. This paper proposes an FPGA-based ABR characteristic waveform automatic identification device. The device integrates an ABR automatic identification algorithm, which outputs the latencies of waves I, III, and V with the ABR waveform as input into the system. The algorithm consists of two parts: a filtering algorithm and a U-Net neural network algorithm, achieving an average accuracy of 91.96% on a self-built dataset. Compared to using only the U-Net neural network algorithm, this method reduces the energy consumption by 19.64% on the self-built dataset, which is of great practical value in scenarios that require long-term or repeated ABR characteristic waveform automatic detection tasks.

关键词： Energy consumption Accuracy Power demand filtering filtering algorithms Hardware Microelectronics Object recognition Character recognition Biological neural networks

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Event-Triggered Fast Information Consensus Filter

Event-Triggered Fast Information Consensus Filter

引用

Chinese Control and Decision Conference, CCDC

作者： Di Wang Gang Hao Electronic Engineering Institute Heilongjiang University Harbin Heilongjiang China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

In distributed state estimation for linear systems with multi-sensor networks, the event-triggered fast information consensus filtering algorithm (ET-FICF) is proposed to address the problems of high communication burden and high number of iterations of the information consensus algorithm. The algorithm utilises a distributed fast consensus weighting algorithm based on alternating direction multiplier method (ADMM) to obtain the weight matrix. For the consensus iteration step, a specific trigger mechanism is designed based on hypothesis testing of Gaussian distribution. The proposed ET-FICF algorithm not only effectively reduces the communication burden, but also has a high consensus speed. Finally, the correctness and effectiveness of the proposed algorithm are verified by simulation examples.

关键词： Linear systems Maximum likelihood detection Nonlinear filters filtering algorithms Gaussian distribution Information filters Convex functions

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