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检索条件"主题词=Filtering algorithms"

共 10307 条记录，以下是261-270 订阅

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A Novel Implementation of a Line X-Ray Source and Its Application to Computed Tomography with Linear Scan Trajectories

A Novel Implementation of a Line X-Ray Source and Its Applic...

引用

IEEE International Symposium on Biomedical Imaging

作者： Daxin Shi Yu Zou Yi Yang Medichord LLC Delaware USA

ISBN: (数字)9798331520526

ISBN: (纸本)9798331520533

In this work, we propose a novel implementation of a line xray source and investigate the computed tomographic (CT) image reconstruction algorithms where linear scan trajectories are assumed. In our proposal, a line x-ray source is realized by introducing a new design of an x-ray tube. Compared with the conventional x-ray tube design, the new tube contains a helical fin as the target. When incoming electrons bombard the surface of a rotating helical fin, a sequence of x-ray focal spots will be produced forming a line x-ray source. Equipped with the novel x-ray tube, x-ray CT scanners can be built where linear scan trajectories are assumed. We demonstrate also in this work that multiple linesegment scan trajectory CT reconstruction problems can be readily solved by Katsevich's filtered backprojection (FBP) algorithm.

关键词： Surface reconstruction Computed tomography Reconstruction algorithms filtering algorithms Trajectory Proposals X-ray imaging Image reconstruction Electrons Biomedical imaging

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Synthesis of a Two-Stage Algorithm for Estimating Antenna Array Orientation Angles from GNSS Signals

Synthesis of a Two-Stage Algorithm for Estimating Antenna Ar...

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International Youth Conference on Radio Electronics, Electrical and Power Engineering (REEPE)

作者： Artyom D. Evseev Stepan V. Orobchenko Kirill V. Kochka Alexander A. Chugunov Nikita I. Petukhov Alice O. Kozhevnikova Radio Systems Department National Research University “MPEI” Moscow Russian Federation

ISBN: (数字)9798331531836

ISBN: (纸本)9798331531843

Global Navigation Satellite Systems (GNSS) have become part of everyday human life. It is impossible to imagine transportation, unmanned aerial vehicles, as well as land surveying and geodesy without GNSS. In addition to determining the exact location of objects, GNSS receiver is used to solve the problem of determining the user's orientation angles from signals. The mode of determining the spatial orientation of mobile objects based on the results of measuring the parameters of navigation satellite (NS) received by spatially separated antennas is one of the most promising directions for expanding the functionality of GNSS. Both one-step and filtering algorithms for estimating consumer spatial orientation are common today. Thus, the purpose of this paper is to carry out the synthesis of a two-step algorithm for estimating antenna array orientation angles from GNSS signals, and to carry out simulation modeling of the synthesized algorithm. The object of the study is a two-step algorithm for estimating the orientation angles of an antenna array. As a result of the study, a two-stage algorithm for antenna array orientation angle estimation was developed and simulation modeling was performed. The root-mean square deviation of the course angle estimates was 0.01 degrees.

关键词： Antenna measurements Global navigation satellite system Satellite antennas Satellites Simulation Transportation Receiving antennas filtering algorithms Antenna arrays Signal to noise ratio

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Better Exploiting Spatial Separability in Multichannel Speech Enhancement with an Align-and-Filter Network

Better Exploiting Spatial Separability in Multichannel Speec...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Ching-Hua Lee Chouchang Yang Yashas Malur Saidutta Rakshith Sharma Srinivasa Yilin Shen Hongxia Jin AI Center-Mountain View Samsung Electronics

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Multichannel speech enhancement (SE) techniques combine multiple microphone signals to extract clean speech from noisy mixtures based on spatial filtering. As the target speech may come from arbitrary, unknown directions, current deep learning-based SE systems could suffer from performance bottleneck in denoising speech within one stage. In contrast, conventional signal processing algorithms often feature a two-stage design, where the first stage focuses on spatially aligning the received signals with respect to the speech source, followed by the second stage to filter out noise. In this paper, we introduce Align-and-Filter network (AFnet) for deep learning-based SE that decouples the primal denoising problem into two sub-problems, which imitates the alignment-followed-by-filtering wisdom from signal processing. The key is to leverage the relative transfer functions (RTFs) that encode meaningful spatial information via a tactically designed alignment strategy. Experimental results show that by leveraging the proposed RTF-based spatial alignment supervision, AFnet learns interpretable directional features to better exploit spatial separability of sound sources for improved SE performance.

关键词： Uncertainty Noise reduction Noise Transfer functions Signal processing algorithms Speech enhancement filtering algorithms Information filters Noise measurement Microphones

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kXpert Profiling System using Unsupervised Keyword Extraction

kXpert Profiling System using Unsupervised Keyword Extractio...

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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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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...

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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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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 Modified Gain Normalized Step Size Adaptive Algorithm for Improved Online Secondary Path Modelling in Active Noise Control

A Modified Gain Normalized Step Size Adaptive Algorithm for ...

引用

International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Asutosh Kar Gagandeep Singh Pradeep K. Shill Somanath Pradhan Vasundhara M. G. Christensen Department of Electronics and Communication Engineering Dr. B. R. Ambedkar National Institute of Technology Jalandhar Punjab India Department of Electrical Engineering Indian Institute of Technology Patna Bihar India Department of Electronics and Communication Engineering National Institute of Technology Warangal Telangana India Department of Electronic Systems Aalborg University Aalborg Denmark

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

The noise cancellation performance of an active control system decreases when there are temporal variations in the primary and secondary paths. An active noise control (ANC) framework has been introduced in this work, which incorporates four adaptive filters and two decorrelation filters for online secondary path modelling. A novel adaptive algorithm for an active noise control filter has been developed with the combination of modified gain filtered-x recursive least square and normalised step size filtered-x least mean square. The aim is to improve the reduction of mean noise and decrease residual noise while maintaining consistent convergence rate. To update the decorrelation filters in the framework, an adaptive variable step size modified decorrelation normalised least mean square algorithm has been used. These filters are designed to maximize the efficiency of secondary path modelling. Compared to its counterparts, the simulation results illustrate the enhancements of the proposed framework without a substantial increase in overall computational complexity.

关键词： Adaptation models Filters Computational modeling Noise Signal processing algorithms Adaptive filters filtering algorithms Decorrelation Computational complexity Convergence

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

A Proportionate Adaptive Conjugate Gradient Algorithms for S...

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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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Water Quality Prediction and Suggesting Filter using Machine Learning

Water Quality Prediction and Suggesting Filter using Machine...

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Intelligent Data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： Archana Chaudhari Rutuja Mane Anant Khot Anup Kadam Nagraj Rajam Department of Instrumentation Engineering Vishwakarma Institute of technology Bibwewadi Pune Maharashtra India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

Survival of all living beings and efficient working of industries and agriculture are largely dependent on the availability of clean water. However, contamination is a major issue that requires dependable methods for assessing the quality of water before its use in drinking, chemical applications, or animal hydration. This research utilizes machine learning to predict water quality based on parameters such as pH, turbidity, hardness, conductivity, and dissolved particles. Based on a broad dataset, models such as time-series analysis and Random Forest classifier are applied to categorize water as safe or unsafe for domestic use. A hardware system equipped with sensors captures real-time data, which enables dynamic assessment of water quality. The proposed solution shows high accuracy in its evaluation using metrics such as Mean Squared Error (MSE), Root Mean Squared Error (RMSE), and Regression Analysis, offering a practical approach to ensure water safety in diverse applications.

关键词： Time series analysis Turbidity filtering algorithms Information filters Water pollution Hardware Sensor systems Sensors Safety Random forests

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Cooperative Multi-Target Tracking Based on Multi-Detection TPHD in MIMO-OFDM Systems

Cooperative Multi-Target Tracking Based on Multi-Detection T...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Chen Zhong Lan Tang Ying-Chang Liang School of Electronic Science and Engineering Nanjing University Nanjing China Center for Intelligent Networking and Communication (CINC) University of of Electronic Science and Technology of China Chendu China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

This paper presents a passive multiple trajectories tracking system with multi-input multi-output orthogonal frequency division multiplexing (MIMO-OFDM) signals transmitted by the base station (BS). Firstly, we propose a Bayesian learning method to obtain the coarse estimations of targets and clutter, which are utilized for trajectories tracking. Considering the potential for a target to generate multiple measurements in overlapping areas of sweeping beams and non-Poisson clutter, we extend the trajectory probability hypothesis density (TPHD) filter to multi-detection TPHD (MD-TPHD) filter with non-Poisson clutter and provide its Gaussian mixture implementation. Simulation results show the performance of the algorithm.

关键词： Learning systems Target tracking Trajectory tracking Simulation filtering algorithms MIMO Trajectory Bayes methods Clutter Speech processing

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