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检索条件"主题词=Filtering algorithms"

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Algorithm for Changing the Size of a Multi-Element Aperture of a Two-dimensional Recursive-Separable Five-Stage Filter for Digital Image Processing

Algorithm for Changing the Size of a Multi-Element Aperture ...

引用

Annual Siberian Russian Workshop on Electron Devices and Materials (EDM)

作者： Andrey V. Kamenskiy Kristina S. Kupriyanova Andrey V. Podnebesnyy Mikhail I. Kuryachiy Natalya Borodina Akaeva M. Tatyana Dept. of Television and Control Tomsk State University of Control Systems and Radioelectronics Tomsk Russia

ISBN: (数字)9798350389234

ISBN: (纸本)9798350353051

The paper presents a description of the developed algorithm for changing the size of a multi-element aperture of a recursive-separable five-stage filter for processing digital images generated by specialized optical systems. The developed algorithm has two features: it has the ability to change the size of a multi-element aperture during use; it makes it possible to use the recursive and separable properties. These capabilities make it possible to reduce the processing time of incoming data, which has a positive effect on the efficiency of the optical-electronic imaging system used. The paper presents a block diagram of a two-dimensional recursive-separable five-stage filter, with the help of which an algorithm was developed for changing the size of a multi-element aperture, and a study of the influence of the aperture size on the performance of the developed filter was carried out. As part of the performance evaluation, the developed algorithm was compared with the classical two-dimensional convolution algorithm. Developed algorithm was tested on three test images of different sizes and formats: $1300 \times 700$ Bitmap Picture, 1200x1200 Tagged Image File, 2900x1900 Joint Photographic Experts Group. During the processing of test images, the dimensions of the multi-element aperture of the developed filter changed. As the aperture size increases, the performance evaluation results also increase. This shows that speeding up the algorithm is an actual task. However, the developed algorithm takes less time than the classical two-dimensional convolution algorithm, from which it can be concluded that the developed solution is effective for both conventional images and images from optoelectronic systems.

关键词： Optical filters Performance evaluation Convolution Digital images Image processing Apertures filtering algorithms

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A High-Reliability Video Auto-Scaling Hardened Design

A High-Reliability Video Auto-Scaling Hardened Design

引用

Computer Science, Electronic Information Engineering and Intelligent Control Technology (CEI), IEEE International Conference on

作者： Xianlong Ding Xin Chen Liangchen Ge Yijun Jiang Nanjing University of Aeronautics and Astronautics Nanjing China

ISBN: (数字)9798350378542

ISBN: (纸本)9798350378559

Energetic particles impacting avionics video processing design systems in the radiation environment possibly produce single-event upsets, leading to partial dysfunction. To address this problem, this paper proposes a high-reliability video auto-scaling hardened design based on the Canny filter auto-scaling platform, using approximate truncation hardened design, Multi-Boot type RAM hardened design, approximate FIR RPR hardened design and incorporating edge information hardened design. Experiments in this paper demonstrate that compared to traditional hardened design and canny-scaling algorithm, this new hardened design has better applicability with an improved PSNR of 3.2992, a reduced BRAM of 33.5, and a reduced LUT of 9425.

关键词： Interpolation Radiation hardening (electronics) Finite impulse response filters Nonlinear distortion Single event upsets Random access memory filtering algorithms Information filters Table lookup Intelligent control

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Design of Event-Based Resilient Distributed filtering Algorithm for Time-Varying Stochastic Systems with Correlated Noises over Sensor Networks

Design of Event-Based Resilient Distributed Filtering Algori...

引用

IEEE International Conference on Cloud Computing and Intelligence Systems (CCIS)

作者： Zehao Li Jun Hu Jiaxing Li Peixia Gao Ruijie Dong Department of Applied Mathematics Harbin University of Science and Technology Harbin China School of Automation Harbin University of Science and Technology Harbin China

ISBN: (纸本)9781665456579

An event-triggered (ET) recursive distributed filtering approach is designed for a class of stochastic systems with correlated noises. The correlated noises are represented by known matrices and the Kronecker $\delta$ function. The ET mechanism that can regulate the sensor information is employed. In addition, the perturbation of the filter gain is considered to suppress the effects of the gain variation on filtering accuracies. An upper bound with respect to the filtering error covariance that can be minimized is obtained by properly choosing the filter gain. Finally, an illustrative example is given to verify the usefulness of the proposed filtering approach.

关键词： Upper bound Stochastic systems Perturbation methods Neural networks Machine learning filtering algorithms Information filters

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Ensemble Feature Selection based Lightweight IDS Tailored for DDoS Attacks Detection over IoT Devices

Ensemble Feature Selection based Lightweight IDS Tailored fo...

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Visualization, Informatics and Technology Conference (IVIT), International

作者： Mahawish Fatima Osama Rehman Ibrahim M. H Rahman Department of Software Engineering Bahria University Karachi Pakistan The Open Polytechnic of New Zealand Wellington New Zealand

ISBN: (数字)9798350354447

ISBN: (纸本)9798350354454

The attack surface has grown due to the widespread use of weak Internet of Things (IoT) devices, and distributed denial of service (DDoS) attacks are becoming more common. The necessity for adaptive intrusion detection systems (IDS) that are effective at detecting threats and need less resources is highlighted by the increase in attacks, particularly for IoT devices with limited resources. Although feature selection (FS) techniques are widely used for creating lightweight intrusion detection systems (IDS), depending solely on one approach can be dangerous and lead to bias in the dataset. Therefore, a flexible and varied FS approach is required. ELIDS (Ensemble Feature Selection for Lightweight IDS), an Ensemble FS strategy that utilizes the advantages of seven different filter-based techniques, is presented in this work. The primary goal of ELIDS is to choose the most important features found by each FS approach. This leads to build strong classification models, which are then thoroughly assessed for both performance and resource efficiency using both in-domain and cross-domain testing. The evaluation findings demonstrate that the suggested model reaches a peak accuracy of 100% for in-domain testing in addition to being lightweight. Cross-domain testing, however, shows that classifiers constructed using individual FS methods suffer a notable reduction in accuracy, while ELIDS-based classifiers exhibit robustness and significantly exceed current methods. Specifically, ELIDS-based classifiers outperform other models by 24%, particularly when Random Forest (RF) is used as the learning technique.

关键词： Visualization Accuracy Machine learning algorithms Intrusion detection filtering algorithms Feature extraction Denial-of-service attack Internet of Things Classification tree analysis Testing

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Structural Simplification of Finite State Machines using Pruning Operators based on Semi-Tensor Product of Matrices

Structural Simplification of Finite State Machines using Pru...

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IEEE International Conference on Control Science and Systems Engineering (CCSSE)

作者： Shuaibing Zhang Yongyi Yan Penglei Hao Jumei Yue College of Information Engineering Henan University of Science and Technology Luoyang China College of Agricultural Equipment Engineering Henan University of Science and Technology Luoyang China

ISBN: (数字)9798331517199

ISBN: (纸本)9798331517205

In this paper, we consider the problem of structural simplification of finite state machines (FSMs), aiming at designing a structural simplification filter for FSMs by constructing pruning operators within the framework of the semi-tensor product of matrices (STP), where the FSM is considered as a logical dynamical system. The concept of pruning operators is proposed by incorporating the physical meaning of FSM state transitions into its dynamic equations. Therefore, to simplify the FSM state space, we construct pruning operators for eliminating redundant states and their additional transitions, respectively. In addition, we further design the corresponding algorithms based on these mathematical descriptions to make the physical meaning of FSM state-space optimization clearer. The validity and correctness of the conclusions are verified using the corresponding language models. The proposed pruning operators lay the foundation for performing state-space optimization and may have a wide range of application scenarios.

关键词： filtering Heuristic algorithms Automata Process control filtering algorithms Control systems Mathematical models Explosions Dynamical systems Optimization

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EM Sensitivity Analysis for a Four-Pole Waveguide Filter Based on Finite-Element Method

EM Sensitivity Analysis for a Four-Pole Waveguide Filter Bas...

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IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications (IMWS-AMP)

作者： Jianguo Xue Feng Feng Mutian Li Shaochang Liu Kaixue Ma Qi-Jun Zhang School of Microelectronics Tianjin University Tianjin China Department of Electronics Carleton University Ottawa ON Canada

ISBN: (数字)9798331520717

ISBN: (纸本)9798331520724

Electromagnetic (EM) sensitivity is crucial for EM optimization, making the rapid acquisition of sensitivity information essential for accelerating the optimization process. Traditional EM sensitivity analysis methods require repeatedly solving large equations, making the process very time-consuming. The efficiency of solving large linear systems can be significantly enhanced by applying various model order reduction (MOR) algorithms. This paper presents an advanced EM sensitivity analysis method to improve the efficiency of multi-frequency EM sensitivity analysis. This method can achieve fast frequency sweep of EM sensitivity analysis and is compatible with a variety of moment-matching MOR algorithms. A four-pole waveguide filter was selected as an example to conduct the sensitivity analysis using this method of sensitivity analysis.

关键词： Radio frequency Linear systems Sensitivity analysis Electromagnetic waveguides filtering algorithms Microwave theory and techniques Mathematical models Microwave filters Electromagnetics Optimization

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Neural Network Control for Efficient Power Management of Renewable Energy Sources in Microgrids

Neural Network Control for Efficient Power Management of Ren...

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International Middle-East Power System Conference, MEPCON

作者： Mohamed Maghraby Ahmed. A. Hossam-Eldin Alexandria Water Company (AWCO) Alexandria Egypt Electrical Engineering Department Alexandria University Egypt

ISBN: (数字)9798350379648

ISBN: (纸本)9798350379655

The use of solar energy with storage system to generate electricity has increased significantly. But due to the high cost of batteries. particularly in, the field of photovoltaic grid-connected systems the increase is still moderate. The main goal of this research is to simulate the performance of grid-connected single-phase, one-stage photovoltaic (PV) systems under various meteorological conditions. Constraints on measuring the system operational efficiency on measuring the systems' operational efficiency. This work focuses on boosting power extraction utilizing extremely effective Maximum Power Point Tracking (MPPT) algorithms. The investigation compares more sophisticated techniques like the Artificial Neural Network algorithm (ANN) with more conventional methods like Incremental Conductance (IncCond) and Perturb and Observe (P&O). In order to determine the ideal filter parameters. It is necessary to build and operate a passively damped LCL filter. Building a connection between an inverter, resistive and inductive loads. and the public utility grid allows the project to investigate alternate methods of controlling active and reactive powers.

关键词： Maximum power point trackers Renewable energy sources Power system management Artificial neural networks Microgrids filtering algorithms Power system stability Harmonic analysis Battery charge measurement Power harmonic filters

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Experimental analysis of quaternion-based attitude estimation algorithms

Experimental analysis of quaternion-based attitude estimatio...

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Chinese Control and Decision Conference, CCDC

作者： Qiuyi Du Bo Ding Yuanchu Wei College of Information Engineering Yangzhou University Yangzhou China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

This paper investigates the performance of quaternion fusion filtering (QFF) and quaternion extended Kalman filtering (QEKF) algorithms on small embedded systems. Firstly, based on the Euler rotation matrix and quaternion rotation matrix, the computational model for the QFF algorithm is provided; Secondly, based on the quaternion state equation and observation equation, the principle of the QEKF algorithm is introduced; Finally, the experiments are designed to analyze the performance of the two algorithms in terms of computational complexity and estimation accuracy. The results show that both attitude estimation algorithms can obtain relatively accurate attitude angles, and the QFF algorithm has less computational complexity and simpler algorithm implementation, while the QEKF algorithm has higher accuracy.

关键词： Accuracy Embedded systems filtering Quaternions Computational modeling Estimation filtering algorithms

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TacVar: Tackling Variability in Short-Interval Timing Measurements on X86 Processors

TacVar: Tackling Variability in Short-Interval Timing Measur...

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IEEE/ACM International Symposium on Cluster Computing and the Grid (CCGRID)

作者： Qiucheng Liao James Lin Center for High-Performance Computing Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798350395662

ISBN: (纸本)9798350395679

When timing short-interval loops, different timing methods may produce different results caused by timing fluctuations. These unstable results prevent us from drawing reliable conclusions in processor performance benchmark. To tackle this issue, we proposed the TacVar framework including three components: 1) we developed the TVkern benchmark to highlight misleading tail-end timing results caused by timing fluctuations; 2) we built the TVconv convolution model to describe the mechanism of coupling between timing fluctuations and performance variability; 3) we designed the TVfilt algorithm to filter out timing fluctuations from measurement results using in-situ timing fluctuation samples. We evaluated TacVar with three TVkern and two real-world stencil kernels on two mainstream X86 processors. The results showed TacVar can reduce measurement deviations caused by timing fluctuations by up to 99.0%.

关键词： Couplings Cloud computing Fluctuations Convolution Benchmark testing filtering algorithms Timing Kernel

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Non-stationary Learning with Multi-layer of Adaptation

Non-stationary Learning with Multi-layer of Adaptation

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International Conference on Electrical and Computer Engineering (ICECE)

作者： Nur Mohammad Mohiuddin Chowdhury Department of Electrical and Electronic Engineering Chittagong University Engineering & Technology Chattogram Bangladesh

ISBN: (数字)9798331531782

ISBN: (纸本)9798331507923

Time-varying system behavior learning is crucial in the current landscape of machine learning, where statistical behavior often lacks precision. This approach effectively models many real-world scenarios characterized by their time-varying non-stationary nature. The focus has shifted towards adaptive systems for these applications, as they demonstrate superior performance compared to traditional fixed-weight systems that have been in use for a longer period. The introduction of multi-layer adaptation has further enhanced the effectiveness of signal processing in this context. A single layer of adaptation utilizing a recursive or steepest-gradient filter is insufficient to ensure both rapid convergence and optimal error fidelity during the learning process, particularly in unknown time-varying environments. Therefore, a multi-layer adaptation approach that combines least mean squares (LMS) and recursive least squares (RLS) algorithms has been proposed, incorporating a mixing parameter [5], [6], [7] that plays a pivotal role in the learning process. This multi-layer adaptation has been shown to significantly improve learning capabilities, achieving approximately 4 to 5 dB better noise fidelity compared to existing single-layer adaptation methods.

关键词： Adaptation models Adaptive systems Noise Adaptive filters Signal processing algorithms Machine learning filtering algorithms Approximation algorithms Time-varying systems Convergence

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