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检索条件"主题词=filtering algorithms"

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Dynamic State Monitoring for Substation Operation Safety: A Kalman Filter-Based Approach

Dynamic State Monitoring for Substation Operation Safety: A ...

引用

Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Wei Li Jie Hua Weiwei Peng Chenghao Feng Foshan Power Supply Bureau of Guangdong Power Grid Co. Ltd. Foshan Guangdong China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

With the increase in the complexity of power systems, the security and reliability of substation operations have become key issues in grid operation. In this paper, a dynamic environment sensing and operation calibration method based on multi-source data fusion is proposed. By integrating temperature, humidity, vibration and other sensor data, the denoising and fusion processing of multi-source data is realized by using Ensemble Kalman Filter (EnKF) technology to monitor the substation environment and equipment status in real time. For accidental anomaly data points, this paper adopts Hampel filter for filtering, and combines the improved DBSCAN algorithm to detect the continuity anomaly data set, effectively identifying the defects and faults of the equipment. The method improves the accuracy and real-time performance of substation fault detection, and can provide strong support for the safe operation and operation optimization of the power grid.

关键词： Temperature sensors Substations filtering Heuristic algorithms Power system dynamics Data integration filtering algorithms Real-time systems Safety Kalman filters

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A Proportionate Adaptive Conjugate Gradient algorithms for Sparse Systems with Impulsive Noise

A Proportionate Adaptive Conjugate Gradient Algorithms for S...

引用

National Conference on Communications (NCC)

作者： Shila Dhande Rajib Lochan Das Department of Electronics and Communication DAIICT Gandhinagar India Department of Electronics KJSSE Somaiya Vidyavihar University Mumbai India

ISBN: (数字)9798331536015

ISBN: (纸本)9798331536022

Tukey's biweight M-estimate conjugate gradient method (TbMCG) is one of the best algorithms to identify the systems with colored input in an impulsive noise environment. In this algorithm, Tukey's biweight M-estimator function is used to im-prove convergence rate and steady-state error in an impulsive environment with less complexity. However, the TbMCG algorithm does not exploit sparse systems though in practice many systems are found to be sparse, such as network echo cancellation, hands-free telephony acoustic echo cancellation, HDTV, wireless multipath channels, underwater acoustic communication, etc. In this paper, proportionate idea is incorporated in the cost function of the TbMCG algorithm to provide proportionate gain to filter taps. The proposed algorithm, called as Tukey's biweight M-estimate proportionate conjugate gradient method (TbMPCG) improves the overall convergence rate by allowing active taps to converge faster. The proposed TbMPCG algorithm also reduces the excessive mean square error (EMSE). Simulation results show that, in particular, the proposed TbMPCG algorithm improves the performance of the TbMCG algorithm both in terms of convergence rate and steady-state error.

关键词： Wireless communication Gradient methods Echo cancellers Noise Adaptive filters filtering algorithms Steady-state Underwater acoustics Gain Convergence

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kXpert Profiling System using Unsupervised Keyword Extraction

kXpert Profiling System using Unsupervised Keyword Extractio...

引用

International Conference on Ubiquitous Information Management and Communication (IMCOM)

作者： Nur Atiqa Basaruddin Bazilah A. Talip Shahrinaz Ismail Centre for Women Advancement & Leadership (CWAL) Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia Knowledge Artificial Intelligence Learning & Automation (KAiLA) Malaysian Institute of Information Technology Universiti Kuala Lumpur Kuala Lumpur Malaysia School of Technology Asia Pacific Asia Pacific University of Technology and Innovation (APU) Kuala Lumpur Malaysia

ISBN: (数字)9798331507817

ISBN: (纸本)9798331507824

Developing an expert system for identifying experts is crucial for organisation especially higher institution. Finding an expert is challenging because some of the researchers are not frequently update their profile, which significantly influenced on potential research collaboration and student intake in post-graduate studies. This impact has indirectly shown the importance of implementing new method in search for experts, with expertise verified by trusted information resources. The kXpert profiling framework is proposed as a design of a new expert finding system using unsupervised keyword extraction algorithm and data filtering. The algorithms used in this system were RAKE, YAKE and Key-BERT, in which KeyBERT is found to be the most accurate among the three algorithms. The system is expected to reduce the time and effort required to engage in discussion with an individual to determine whether he or she is the correct expert in need

关键词： Accuracy Information resources Tagging filtering algorithms Information filters Classification algorithms Information management Data mining Object recognition Expert systems

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A Sigmoid Filter Proportionate Normalized LMS Algorithm for Sparse Systems

A Sigmoid Filter Proportionate Normalized LMS Algorithm for ...

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International Conference on Signal Processing and Communication (ICSC)

作者： Ansuman Patnaik Rosalin Deepak Kumar Rout Satish Kumar Gannamaneni School of Electronics Engineering KIIT Deemed to be University Bhubaneswar India School of Electronics Science OUTR Bhubaneswar India

ISBN: (数字)9798331511890

ISBN: (纸本)9798331511906

Formerly, a least mean square algorithm employing a sigmoid framework (SLMS) was developed to cope with the impulsive noise. However, the SLMS technique was sparse agnostic, and the LMS approach has a gradient noise amplification issue. To address the point, the SLMS algorithm is updated to sigmoid normalized LMS (SNLMS), and to adjust for sparsity, a filter proportionate adaptation principle is applied to the SNLMS method, yielding the SFPNLMS algorithm. Finally, simulation results show that the innovative SFPNLMS technique is more resistant in an impulsive environment and has a rapid convergence for identification of the sparse systems than other current algorithms.

关键词： Resistance Adaptive systems Simulation Noise Signal processing algorithms Interference filtering algorithms System identification Convergence

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The Novel Iterative Two-Stage Algorithm with Neighborhood Correlation for Removal the AAIN (Arbitrary Amplitude Impulse Noise)

The Novel Iterative Two-Stage Algorithm with Neighborhood Co...

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International Electrical Engineering Congress (iEECON)

作者： Vorapoj Patanavijit Darun Kesrarat Kornkamol Thakulsukanant Kanabadee Srisomboon Wilaiporn Lee Assumption University of Thailand Thailand Department of Electrical and Computer Engineering Faculty of Engineering King Mongkut's University of Technology North Bangkok Bangkok Thailand

ISBN: (数字)9798331543952

ISBN: (纸本)9798331543969

Within outlier removal experimentation association, in the outlier revelation mechanism, the investigated figuring basis (which is located at the midpoint of the investigated window) and its neighborhood correlation (which is estimated from the investigated figuring basis and its encircling figuring basis) are theoretically elucidated as outlier correlation. One of the ultramodern and most energetic of noise removal algorithms is an original two-stage noise removal algorithm stand on the neighborhood correlation, which was introduced in 2020 for AAIN (Arbitrary Amplitude Impulse Noise). Thereby, this paper proposes the novel iterative two-stage algorithm with neighborhood correlation, which is progressed from the original two-stage noise removal algorithm, for removal the AAIN. In the simulated investigation, copious digital figures, which are compounded of F16 and Pepper under all random noise proportion, are engaged in the novel iterative two-stage algorithm in contemplating of the energetic of precedent state-of-art algorithms: MF, SMF, AMF and original 2-Stage system. From these simulated investigation products, the noise removal algorithm based on novel iterative 2-stage algorithm constitutes the exclusive energetic, which is contemplated with precedent state-of-art algorithms.

关键词： Electrical engineering Correlation Digital images Noise Noise reduction Adaptive filters filtering algorithms Iterative algorithms

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Generalized Approach for Fractional-Order Low-Pass Butterworth Filter Realization with an Inverse Follow the Leader Filter (IFLF) Topology

Generalized Approach for Fractional-Order Low-Pass Butterwor...

引用

IEEE Southeastcon

作者： Rowan Aldridge David Kubánek Jaroslav Koton Todd J. Freeborn Dept. Elec. Computer Eng. The University of Alabama Tuscaloosa USA Dept. Telecommunications Brno University of Technology Brno Czech Republic

ISBN: (数字)9798331504847

ISBN: (纸本)9798331504854

This research presents a generalized approach to determine the coefficients to realize any $(N+\alpha)$ fractional-order low-pass Butterworth response using transfer function forms based on the Inverse Follow the Leader Filter (IFLF) topology. This approach automates the process to create and assemble the required transfer function (based on user specified values) and then apply a numerical optimization to estimate the necessary coefficients to achieve the target filter magnitude response. MATLAB simulations of $(2+\alpha)$ and $(10+\alpha)$ order filters using the generalized approach validate the process. Further, an experimental 2.5-order low-pass filter is experimentally realized (using an approximated fractional-order capacitor) to validate the characteristics of a low-pass filter designed using this process.

关键词： Capacitors Low-pass filters Transfer functions filtering algorithms Approximation algorithms Topology Numerical models MATLAB Integrated circuit modeling Optimization

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Conditions of Informational Signal Receiving by Land Based Adaptive Antenna Arrays of Global Navigation Satellite Systems

Conditions of Informational Signal Receiving by Land Based A...

引用

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

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

ISBN: (数字)9798331518752

ISBN: (纸本)9798331518769

This paper presents a methodology for assessing the possibility to receive the signals from the Global Navigation Satellite Systems (GNSS) by the receivers with the Adaptive Antenna Arrays (AAA). The methodology is based on the estimation of the steady-state Signal-to-Noise Ratio (SNR) at the AAA output. The SNR is estimated over all the possible directions of the signal source angular locations. This methodology is demonstrated by using the examples of the steady-state behavior of the widely used Side Lobe Canceller (SLC) AAA and the Linearly Constrained (LC) AAA with the beam constraint. The simulation demonstrates that the satellite signals can be received from about 30% directions of the spherical angular space in the case of a rectangular AAA with $2 \times {4}$ antennas after the suppressing of 7 interfering signals. It is about a 10% bigger value comparing to that of the AAA in the initial nonadaptive stage. If to consider the upper hemisphere of space only, then this value is doubled. In this experiment, both of the considered AAA demonstrate about the same performance from the interference suppression and informational signals receiving points of view. This efficiency might be different in another scenario. The generic architecture and computational procedures of the AAA used in the considered simulations and computations are also presented. The procedures are based on the usage of the Recursive Least Squares adaptive filtering algorithm.

关键词： Interference suppression Global navigation satellite system Satellite antennas Adaptive systems Satellites Adaptive arrays Receiving antennas filtering algorithms Steady-state Signal to noise ratio

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Novel Method for FIR Notch Filter Design Using Firefly Algorithm

Novel Method for FIR Notch Filter Design Using Firefly Algor...

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Power Electronics, Computer Applications (ICPECA), IEEE International Conference on

作者： Haijiang Hu Yanchun Wang Cheng Ma Qiang Wang College of Electronic and Electrical Engineering Bengbu University Bengbu China

ISBN: (数字)9798331533694

ISBN: (纸本)9798331533700

Notch filter is an important type of filter which is widely used in communication technology and other fields because it effectively filters out the interference signals with the specific extremely narrow frequency bands, and efficiently transmits signals outside these frequency bands. A novel optimization method for FIR notch filter design using Firefly Algorithm is proposed. This method uses the minimum magnitude error in stopband as the optimization object, uses the magnitude error in passband as the constraint conditions, and realizes the FIR notch filter design by Firefly Algorithm. The result of design has both small order and good performance. Therefore this method can be employed in the FIR notch filter design efficiently.

关键词： Finite impulse response filters Design methodology Signal processing algorithms Optimization methods Interference filtering algorithms Signal processing Power electronics Passband Notch filters

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Binary Learning Cooking Algorithm with Relief for Feature Selection of High-dimensional Gene Expression Data

Binary Learning Cooking Algorithm with Relief for Feature Se...

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Emerging Smart Computing and Informatics (ESCI), Conference on

作者： Bibhuprasad Sahu Swagatika Dalai Amrutanshu Panigrahi Abhilash Pati Chetan Aher JVR Ravindra Dept. of Information Technology Vardhaman College of Engineering Hyderabad India Department CSE KIIT Polytechnic Bhubaneswar Odisha India Department CSE Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar Odisha India Department CSE AISSMS Institute of Information Technology Pune Maharashtra India Dept. of ECE Vardhaman College of Engineering Hyderabad India

ISBN: (数字)9798331515683

ISBN: (纸本)9798331515690

Feature selection (FS) has a significant impact on machine learning. The objective is to find the most important features while maintaining high classification accuracy by identifying the possible fewest features from the high-dimensional dataset. Researchers prefer to use the filter-wrapper model by considering different metaheuristic methods for accurate feature selection. But in some cases, the proposed algorithms become less productive and achieve high time complexity. This paper presents a hybrid model of Relief with Binary Learning Cooking Algorithm (BLCA) to select optimal features. The algorithm builds on the Learning cooking algorithm (BLCA), a new optimization method inspired by the learning process "How to learn cooking". We tested how well this method responds to FS challenges in high-dimensional datasets using six cancer datasets, many with different ranges of features. We compared different existing FS algorithms with R-BLCA using accuracy, precision, sensitivity, specificity, and F-Score. The results show that the proposed algorithm performs better than other FS methods with an accuracy of 99. 91% for the SRBCT dataset.

关键词： Support vector machines Accuracy Sensitivity Optimization methods filtering algorithms Feature extraction Classification algorithms Object recognition Time complexity Cancer

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Research on Automatic Landing and Positioning of Indoor Substation Inspection Unmanned Aerial Vehicle Based on Machine Vision Assisted Technology

Research on Automatic Landing and Positioning of Indoor Subs...

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Electrical Automation and Artificial Intelligence (ICEAAI), International Conference on

作者： Zhong Xie Rizhao Wang Zhipeng Xu Xuzhou new electric power Co. Ltd. Xuzhou China Jiangsu Xudian Construction Group Co. Ltd. Fengyang Technology Company Xuzhou China

ISBN: (数字)9798331506797

ISBN: (纸本)9798331506803

If the indoor substation inspection drone deviates from the predetermined position during landing, it may collide with important and expensive equipment such as distribution cabinets and transformers in the substation room, causing damage and affecting the stability of power supply. To this end, a method for automatic landing and positioning of indoor substation inspection unmanned aerial vehicles based on machine vision assisted technology is studied. Capture and transmit landing information of indoor substation inspection unmanned aerial vehicles through multispectral cameras and self-organizing network communication technology; Gaussian filtering, wavelet decomposition, and bilateral filtering algorithms based on machine vision assisted technology are used to enhance drone landing images; Constructing a reference coordinate system for automatic landing and positioning of indoor substation inspection drones; The center position of the landing target is determined using a kernel correlation filter, and the landing image is segmented. The residual learning network is used to optimize the automatic landing positioning of the indoor substation inspection drone. The experimental results show that after enhancing the drone image, the brightness, contrast, and clarity of the image are significantly improved; The landing position coordinates obtained by this method are relatively close to the actual position coordinates, with small average center offset and average positioning error, which improves the accuracy of automatic landing positioning for indoor substation inspection drones.

关键词： Substations Accuracy Power supplies Brightness Inspection filtering algorithms Self-organizing networks Autonomous aerial vehicles Transformers Drones

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