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检索条件"主题词=filtering algorithms"

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Influence of Primary and Secondary Path Estimation Accuracy on Active Noise Control Performance

Influence of Primary and Secondary Path Estimation Accuracy ...

引用

Systems of Signals Generating and Processing in the Field of on Board Communications

作者： Victor I. Djigan Institute of Microdevices and Control Systems National Research University of Electronic Technology Moscow Russia

ISBN: (数字)9798331532635

ISBN: (纸本)9798331532642

An Active Noise Control (ANC) system based on a modified architecture is considered. This architecture allows to accelerate the convergence of the adaptive filtering algorithms in use. Besides, it allows to use the most efficient Recursive Least Squares adaptive filtering algorithms which provide the fastest convergence comparing to the gradient search-based adaptive algorithms. The architecture of the ANC system and its mathematic description are presented. The simulation results demonstrate the ANC system performance. It is shown, that the number of the adaptive filter weighs can be decreased about 30% of the theoretically required value without any observable loss of the ANC performance. This is possible because of fading shape of the primary and secondary path acoustic impulse responses. As the result, the contribution of the impulse response “tails” to the signals at the error microphone of the ANC system is comparable with that of the ambient noise. This also allows to decrease the required number of the adaptive filter weights and to decrease the computational resources required to the implementation of the ANC system.

关键词： Shape System performance Simulation Noise Adaptive filters Computer architecture Tail filtering algorithms Control systems Convergence

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Using ML filters to help automated vulnerability repairs: when it helps and when it doesn’t

Using ML filters to help automated vulnerability repairs: wh...

引用

IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Technologies Results Track (ICSE-NIER)

作者： Maria Camporese Fabio Massacci University of Trento IT Vrije Universiteit Amsterdam NL

ISBN: (数字)9798331537111

ISBN: (纸本)9798331537128

[Context:] The acceptance of candidate patches in automated program repair has been typically based on testing oracles. Testing requires typically a costly process of building the application while ML models can be used to quickly classify patches, thus allowing more candidate patches to be generated in a positive feedback loop. [Problem:] If the model predictions are unreliable (as in vulnerability detection) they can hardly replace the more reliable oracles based on testing. [New Idea:] We propose to use an ML model as a preliminary filter of candidate patches which is put in front of a traditional filter based on testing. [Preliminary Results:] We identify some theoretical bounds on the precision and recall of the ML algorithm that makes such operation meaningful in practice. With these bounds and the results published in the literature, we calculate how fast some of state-of-the-art vulnerability detectors must be to be more effective over a traditional AVR pipeline such as APR4Vuln based just on testing.

关键词： Feedback loop Pipelines Machine learning Detectors Maintenance engineering Predictive models filtering algorithms Reliability theory Testing Software engineering

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Designing Multi-Channel Filter for Processing Coherent Pulse Train with Staggered Pulse Repetition Frequency On FPGA

Designing Multi-Channel Filter for Processing Coherent Pulse...

引用

Digital Signal Processing and its Applications (DSPA), International Conference on

作者： Koshelev Vitaly Ivanovich Trinh Ngoc Hieu Federal State Budgetary Educational Institution of Higher Education Ryazan State Radio Engineering University named after V.F. Utkin Ryazan Russian Federation

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

In pulse and digital radio engineering systems, the Doppler frequency of a coherent pulse train (CPT) is measured by the response in a multichannel Doppler filter (MDF) based on the fast Fourier transform (FFT) algorithm. When using a coherent pulse train with different pulse repetition frequency (PRF), the efficiency of signal accumulation in the channels of the traditional FFT algorithm decreases. The coherent pulse train with different PRF will be called a coherent pulse train with staggered PRF. To eliminate this drawback when processing the CPT with staggered PRF, the authors use a modified FFT algorithm that increases the signal-to-noise ratio at the MDF outputs against the background of uncorrelated interference. The report presents the design of a modified FFT algorithm for processing the CPT with staggered PRF on field-programmable gate array (FPGA).

关键词： Fast Fourier transforms Signal processing algorithms Computer architecture filtering algorithms Radar signal processing Frequency measurement Doppler effect Velocity measurement Field programmable gate arrays Signal to noise ratio

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Study on dynamic compensation of marine conductivity sensor based on Particle Swarm Optimization Algorithm

Study on dynamic compensation of marine conductivity sensor ...

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Computer Information Science and Application Technology (CISAT), International Conference on

作者： Kaili Hu Xu Chai Lin Cao Fengxiang Guo Xueyu Zhang Guangsen Xia Xuesong Zhou Mei Zhang Lili Zhang Shousheng Liu Zhigang Gai Qilu University of Technology (Shandong Academy of Sciences) Qingdao China Institute of Oceanographic Instrumentation Qilu Universit of Technology (Shandong Academy of Sciences) Qingdao China

ISBN: (数字)9798350375107

ISBN: (纸本)9798350375114

Aiming at the problem of insufficient response speed of the marine conductivity sensor, a method of designing a dynamic compensation filter model for dynamic compensation is proposed to improve the response speed of the sensor. The dynamic response curve of the sensor was measured by the marine sensor time constant measurement device, and the dynamic compensation filter model of the conductivity sensor was established by the system inverse modelling method, and the dynamic compensation filter model was optimized by the particle swarm optimization algorithm. The experimental results show that the time constant of the measured sensor is 234.5 ms at a speed of $1 \mathrm{~m} / \mathrm{s}$. After compensation, the sensor time constant is reduced to 27.5 ms, which is about 90%, and the response speed of the sensor is effectively improved.

关键词： Information science Atmospheric measurements Inverse problems Heuristic algorithms Conductivity filtering algorithms Conductivity measurement Particle measurements Time measurement Particle swarm optimization

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A Parameter Optimisation-Based Fault Extraction Method for MNAD Rolling Bearing

A Parameter Optimisation-Based Fault Extraction Method for M...

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Mechatronics Technology and Intelligent Manufacturing (ICMTIM), International Conference on

作者： Xuefeng Mao Chao Jiang Department of Mechanical Engineering Shanghai Dian ji University Shanghai

ISBN: (数字)9798350363265

ISBN: (纸本)9798350363272

Aiming at the problem of fault feature extraction difficulty of rolling bearings under noise, a Minimum noise amplitude deconvolution (MNAD) algorithm based on parameter optimization is proposed. To solve the problem that the two key parameters of the MNAD algorithm, the filter length T and the fault feature frequency α, are not clear, the parameter search is carried out with the maximum Kurtosis value as the optimization goal. Firstly, select and fix the appropriate filter length to search for the optimal parameters of the fault characteristic frequency; secondly, fix the optimal parameters of the fault characteristic frequency, and search for the optimal parameters of the filter length roughly and accurately; lastly, the optimal MNAD algorithm combined with the Hilbert envelope spectrum is used for the fault diagnosis of rolling bearings. The feasibility of the method is proved in the simulation signals and experimental data.

关键词： Fault diagnosis Deconvolution Mechatronics Noise Rolling bearings filtering algorithms Search problems

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Research on Background Electromagnetic Interference Suppression Method Based on MUSIC-LCMV Algorithm

Research on Background Electromagnetic Interference Suppress...

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Progress in Electromagnetic Research Symposium (PIERS)

作者： Quan Deng Qiang-Ming Cai Xin Cao Longjian Zhou Haoran Li Zhen-Yong Du Yixiang Li Yuyu Zhu Yu-Teng Zheng Bo Pu Jun Fan School of Information Engineering Southwest University of Science and Technology Mianyang China Robot Technology Used for Special Environment Key Laboratory of Sichuan Province Mianyang China Tianfu Institute of Research and Innovation Southwest University of Science and Technology (SWUST-TIRI) China Chengdu Juji Millimeter Wave Technology Co. Ltd Chengdu China DeTooLIC Technology Co. Ltd Ningbo China

ISBN: (数字)9798350375909

ISBN: (纸本)9798350375916

Accurately extracting the electromagnetic radiation signal of the equipment to be tested from the environmental electromagnetic signal is one of the difficult problems that urgently need to be solved when conducting electromagnetic compatibility on-site testing. Virtual darkroom technology can accurately receive radiation information from the tested equipment in a noisy environment. However, there may be significant errors in the test results when there are strong interference signals. Based on the principle of spatial cancellation, this paper proposes a new method for suppressing background electromagnetic interference. This method combines the idea of simultaneously cancelling background noise in a virtual darkroom with the introduction of array signal processing, and uses beamforming as the operating mode to filter out background noise in on-site testing. This algorithm can overcome the shortcomings of traditional methods, that is, it does not need to assume that background noise is not related to the radiation signal of the tested equipment, the spatial distribution of background noise is uniform, and the signal-to-noise ratio is large. By providing less prior information or reference information of the on-site environment, good results can be achieved. Its core is high-precision direction of arrival estimation through multiple signal classification algorithm (MUSIC). After obtaining the direction of the signal, the Linear Constrained Least Variance (LCMV) algorithm is used to weight the signal received by each antenna. The weighted sum of each antenna suppresses background noise and preserves the radiation signal of the tested equipment intact. Finally, the correctness of this method was verified through an example.

关键词： Smoothing methods Graphical models Electromagnetic interference Signal processing algorithms filtering algorithms Electromagnetic compatibility Classification algorithms

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Learning Temporal Consistency Correlation Filter with Gradient Feature for UAV Tracking

Learning Temporal Consistency Correlation Filter with Gradie...

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Computer, Vision and Intelligent Technology (ICCVIT), International Conference on

作者： Yue He Guoxia Xu Lizhen Deng Hu Zhu School of Communications and Information Engineering Nanjing University of Posts and Telecommunications Nanjing China

ISBN: (数字)9798331540043

ISBN: (纸本)9798331540050

This paper presents a novel target tracking model that integrates a learning temporal consistency constraint (LTCF) guided by gradient features, seamlessly embedding it within a correlation filter-based tracking framework. This model incorporates the gradient feature of the correlation filter to enhance information extraction and feature representation in the tracking model for small targets. Additionally, the entire model is effectively solved using an alternating optimization method. To assess the performance of the proposed tracking algorithm, we conduct comparative experiments on LTCF and other tracking models using multiple datasets. The experimental results demonstrate that the LTCF model delivers robust tracking performance in complex scenes, ensuring both accuracy and reliability in target tracking.

关键词： Adaptation models Target tracking Correlation Accuracy Optimization methods filtering algorithms Information filters Feature extraction Autonomous aerial vehicles Reliability

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Efficient Time-frequency Domain Filter Design Against SAR Interference

Efficient Time-frequency Domain Filter Design Against SAR In...

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Signal, Information and Data Processing (ICSIDP), IEEE International Conference on

作者： Xiangyu Zhu Jiadong Wang Yachao Li Endi Zhu Qi Wang Yang Zhang National Key Laboratory of Radar Signal Processing Xidian University Xi’an China Academy of Advanced Interdisciplinary Research Xidian University Xi’an China

ISBN: (数字)9798331515669

ISBN: (纸本)9798331515676

Synthetic aperture radar (SAR) could be easily interfered with by a number of active jamming signals from enemy active jammers during its operating cycle, which seriously affects its battlefield information acquisition capability. In order to effectively combat multiple types of interference, this paper proposed an efficient time-frequency domain filtering method, which extracts the jamming-free pulses from received echo, and constructs an adaptive time-frequency domain filter by using its max time-frequency domain energy peaks, which could accurately extract and suppress interference. Simulation results demonstrate the significant suppression effect of the proposed method on the typical types of interference measured.

关键词： Time-frequency analysis Simulation Interference filtering algorithms Information filters Stability analysis Jamming Time-domain analysis Synthetic aperture radar Signal to noise ratio

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Graph Learning Based Financial Market Crash Identification and Prediction

Graph Learning Based Financial Market Crash Identification a...

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Artificial Intelligence (CAI), IEEE Conference on

作者： Dayu Qin Ercan E. Kuruoglu Tsinghua-Berkley Shenzhen Institute Institute of Data and Information Shenzhen International Graduate School Tsinghua University China

ISBN: (数字)9798350354096

ISBN: (纸本)9798350354102

The recognition and anticipation of financial crises play a pivotal role in safeguarding investor interests and maintaining the normalcy of the market order. Therefore, we aim to learn and predict the market abnormal fluctuation from the perspective of its graph structure. In this study, we simplify the financial complex networks with the Planar Maximally Filtered Graph(PMFG) algorithm and analyze their structural characteristic. Then, we integrate the Ollivier-Ricci curvature (ORC) of each network as a manual feature into a graph learning algorithm. We validate the effectiveness of our proposed methodology and engage in a discussion of the future research directions illuminated by our experimental results.

关键词： Fluctuations Manuals Complex networks Learning (artificial intelligence) Companies filtering algorithms Prediction algorithms

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A Version-Based Algorithm for Quality Enhancement of Automatically Generated Vulnerability Inventories

A Version-Based Algorithm for Quality Enhancement of Automat...

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Cyber Security and Resilience (CSR), IEEE International Conference on

作者： Silvia Bonomi Marco Cuoci Simone Lenti Sapienza University of Rome Rome Italy

ISBN: (数字)9798350375367

ISBN: (纸本)9798350375374

Self-protecting systems heavily depend on the quality of information in input in the adaptation loop. Among the others, device and vulnerability inventories play a fundamental role in such systems, and improving their quality is paramount. This paper proposes a new version-based algorithm to filter out false positives from automatically generated inventories by minimizing the interactions with security experts.

关键词： Greedy algorithms Accuracy filtering algorithms Information filters Security Computer crime Monitoring

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