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International Conference on Communications, Information System and Computer Engineering (CISCE)

作者： Yecheng Lao Kaixuan Lin Guangdong University of Technology Guangdong China

ISBN: (数字)9798350353174

ISBN: (纸本)9798350353181

A hybrid recommendation algorithm based on K-means++ and dynamic temporal weights is proposed to address the problems of data sparsity and low temporal correlation in traditional collaborative filtering recommendation algorithms. The Weight Slope One algorithm fills the score matrix and reduces the data sparsity, then the K-means++ clustering algorithm is used to cluster the filled data, and then the dynamic time weight is introduced into the collaborative filtering recommendation algorithm based on the user and the item and the item and user dependence is adjusted by the $\boldsymbol{\beta}$ adjusting factor, to achieve better stability and accuracy. Experimental results show that the algorithm better solves the problems of sparse rating data, poor recommendation timeliness, and significantly improved recommendation effect.

关键词： Accuracy Heuristic algorithms Collaborative filtering Clustering algorithms filtering algorithms Information filters User experience

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An Ionosphere Correcting Algorithm for GNSS Signals Based on Observable Analysis

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Chinese Journal of Electronics 2023年第1期21卷 185-189页

作者： Shuliang Gao Rui Li Zhigang Huang School of Electronic and Information Engineering Beijing University Beijing China

In order to correct ionosphere error on the GNSS signals, this paper proposes an algorithm to estimate the ionosphere corrections on the basis of the observability analysis. The distributed Kalman filter consisting of some parallel sub-filters is utilized and the ionosphere corrections are obtained from weighting the results of these sub-filters. However, the performance of some sub-filters is degraded by the sub-filters with poor observability. To evaluate the observability of these sub-filters, the Ionosphere observable factor (IOF) is defined and calculated by the eigenvalue decomposition. Moreover, to mitigate the adverse effect from the poor observability and boost the accuracy of estimates, an observability-based weighting strategy is designed and adopted. The simulation result demonstrates that the a significant improvement on the accuracy is gained by the observability-based weighting strategy.

关键词： Global navigation satellite system Simulation Estimation filtering algorithms Eigenvalues and eigenfunctions Kalman filters Indexes

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A Hybrid Adaptive filtering Algorithm based Control Strategy for LVRT Capability Enhancement of Grid-Connected DFIG-WECS

A Hybrid Adaptive Filtering Algorithm based Control Strategy...

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Power and Renewable Energy Conference (IPRECON), IEEE International

作者： Arindam Chakraborty Tanmoy Maity Deparment of Electrical Engineering Indian Institute of Technology (ISM) Dhanbad Dhanbad Jharkhand India

This work proposes a novel application of the hybrid adaptive filtering algorithm (HAFA) that combines both continuous mixed p-norm (CMPN) topology and least mean square root of exponential (LMSRE) strategy in order to improve the low voltage ride-through (LVRT) capability of the grid-connected doubly fed induction generator (DFIG) based wind energy conversion system (WECS). This article suggests the CMPN-LMSRE-based HAFA because of its quick convergence, low computing load, and straightforward construction. Through quick convergence velocity, the proposed HAFA adjusts the gains of all proportional-integral (PI) controllers. Under the cascaded arrangement, four PI controllers are used in the rotor side converter (RSC), and four more are used in the grid side converter (GSC). The RSC is regulated by cascaded structure-based PI controllers to limit generator power loss and enhance power production. In contrast, GSC is controlled to preserve the grid side reactive power and dc-link voltage. By contrasting the outcomes of the proposed CMPN-LMSRE-based PI controllers with those of CMPN-based and LMSRE-based PI controllers during severe grid disturbances, the validity of the proposed CMPN-LMSRE-based PI controllers is confirmed. The MATLAB application is used to carry out the LVRT capability.

关键词： Transient response PI control Doubly fed induction generators Rotors filtering algorithms Hybrid power systems Topology

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Research on Interference Suppression Based on Fractional Fourier Transform Adaptive filtering

Research on Interference Suppression Based on Fractional Fou...

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Frontiers Technology of Information and Computer (ICFTIC), IEEE International Conference on

作者： Hang Yang Yun Zhang Guowei Li Yu Zhou Weifeng Zhu Min Tang North China Institute of Computing Technology Beijing China National Innovation Institute of Defense Technology Beijing China

Fractional fourier transform (FRFT) processing has received extensive attention because of its superior anti-jamming performance. In this paper, in order to meet the demand of signal reception of intelligent wearable emergency search and rescue terminal in complex electromagnetic environment, a simulation study of adaptive filtering algorithm based on fractional Fourier transform is carried out. First, a theoretical model of fractional Fourier transform is established, and then the steps of adaptive filtering algorithm based on fractional Fourier transform are theoretically analyzed. Finally, the anti-interference performance of this method is simulated and studied. It can be seen from the simulation results that when the signal-to-interference ratio is −60dB, the adaptive algorithm based on fractional Fourier transform can still achieve signal reception under strong interference. The research in this paper can provide some reference for the anti-interference design of emergency rescue terminal.

关键词： Interference suppression Adaptation models Analytical models Fourier transforms filtering Simulation filtering algorithms

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A Variable Step Size Logarithmic Hyperbolic Cosine Adaptive filtering-Based Control Scheme for Grid-Tied PV-DSTATCOM to Enhance Power Quality

A Variable Step Size Logarithmic Hyperbolic Cosine Adaptive ...

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International Conference on Power Electronic Drives

作者： Markala Karthik Venkata Ramana Naik N Anup Kumar Panda Department of Electrical Engineering National Institute of Technology Rourkela Odisha India

A variable step size logarithmic hyperbolic cosine adaptive filtering (VSS-LHCAF)-based control scheme is proposed for a grid-tied multifunctional photovoltaic-distribution static compensator (GTPVD) having single-stage topology for solar energy conversion with maximum power extraction from the PV array. The proposed VSS-LHCAF control scheme is utilized to estimate the fundamental weight components of nonlinear load current accurately in generating the driving pulses for the three-phase two-level voltage source converter (VSC) switches employed in GTPVD, thus enhancing the power quality by mitigating the harmonics produced by nonlinear loads, providing a reactive power compensation, unbalanced load compensation, and maintaining grid currents sinusoidal at unity power factor (UPF). The multifunctional GTPVD system is developed in MATLAB/Simulink. The response of GTPVD is observed under solar irradiance variation and unbalanced loading conditions with a nonlinear load. Further, the proposed control scheme is compared with existing adaptive filtering-based algorithms like least mean square (LMS) and least mean fourth (LMF)-based control schemes, and it is observed that proposed control scheme offers better performance in terms of convergence, oscillations, steady-state error, and grid current total harmonic distortion (THD).

关键词： Reactive power Power quality Adaptive filters filtering algorithms Harmonic analysis Steady-state Power harmonic filters

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Research on human posture recognition based on multi-feature fusion chunk sampling particle filtering algorithm

Research on human posture recognition based on multi-feature...

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Frontiers Technology of Information and Computer (ICFTIC), IEEE International Conference on

作者： Yufei Zhao Naval Architecture and Ocean Engineering College Dalian Maritime University Dalian China

As a developing research direction in the field of computer vision, human posture recognition(HPR) involves many related technologies such as pattern recognition, artificial intelligence, image processing and machine vision. This paper focuses on the application of multi feature fusion(MFF) and block sampling(BS) particle filter algorithm(PFA) in HPR, and briefly analyzes the design of human posture data acquisition terminal, the analysis and extraction of human contour features, and the analysis and extraction of stride features; This paper discusses the MFF and BS PFA, and applies it to HPR. Through the statistical experiments of recognition rate(RR) and sensitivity of virtual reality actions, the effectiveness of MFF and BS PFA applied to HPR is verified.

关键词： Sensitivity Heuristic algorithms Machine vision Virtual reality filtering algorithms Feature extraction Information filters

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Speeding up the Throughput of an NLMS Adaptive Filter

Speeding up the Throughput of an NLMS Adaptive Filter

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IEEE International Conference on Consumer Electronics-Taiwan (ICCE-TW)

作者： Yu-Zhe Huang Chia-Yu Yao Ping-Yi Lee Department of Electrical Engineering National Taiwan University of Science and Technology Taipei ROC Graduate Institute of Electronics Engineering National Taiwan University Taipei ROC

ISBN: (数字)9798350386844

ISBN: (纸本)9798350386851

Adaptive filters are widely used in communications, signal processing, and system identifications. The computational bottleneck of the normalized least mean square (NLMS) adaptive filter is the division. Previous works have shown that using the reciprocal approximation for the divisor not only works well for the NLMS algorithm but can also improve the adaptive filter’s overall throughput rate. This work designs a lookup table (LUT) reciprocal approximation method to replace the division for the NLMS adaptive filter. The experimental results show that the adaptive NLMS filter using the proposed approximation consumes less power and resources than the ones using the standard SRT division and the previously reported CSD reciprocal approximation on an FPGA platform.

关键词： Finite impulse response filters Adaptive filters filtering algorithms Throughput Table lookup System identification Approximation methods

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Weighted measurement fusion filter for multi-sensor uncertain systems with time-correlated measurement noises*

Weighted measurement fusion filter for multi-sensor uncertai...

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Chinese Control and Decision Conference, CCDC

作者： Yuhui Wang Jing Ma School of Mathematics Science Heilongjiang University Harbin China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

This paper is concerned with the globally optimal fusion estimation problem for multi-sensor stochastic uncertain systems with time-correlated measurement noises. First, the considered system is transformed into a normal system with uncorrelated white noises. State augmentation and measurement difference are the key technologies. Then based on full-rank decomposition and weighted least-squares method, the weighted measurement fusion filter is proposed in the sense of the linear minimum variance. The proposed weighted measurement fusion filter has lower computational cost and the same accuracy as the centralized one for the same initial values. It is globally optimal. A tracking system example shows the effectiveness of the proposed algorithm.

关键词： Weight measurement Uncertain systems Maximum likelihood detection Measurement uncertainty Nonlinear filters filtering algorithms White noise

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Distributed mccKF based INS/UWB Integrated navigation for quadruped robot

Distributed mccKF based INS/UWB Integrated navigation for qu...

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Robotics, Intelligent Control and Artificial Intelligence (RICAI), International Conference on

作者： Kaixin Liu Maosheng Yang Jingwen Yu Xiangpeng Wang Yuan Xu School of Electrical Engineering University of Jinan Jinan China

ISBN: (数字)9798331541699

ISBN: (纸本)9798331541705

In order to better realize the quadruped robots localization, this paper proposes a combined positioning algorithm based on distributed maximum correntropy Kalman filter(mccKF) and ultra-wideband (UWB) technology for inertial navigation system (INS). The aim is to improve the navigation and positioning accuracy of quadruped robot based on inertial sensors. In this algorithm, the distributed maximum correntropy Kalman filter is used to estimate the position error of INS and UWB. The system parameters are used as the state vector, and the data output of the local mccKF filter is input into the main filter for fusion, and the optimal estimate is given. The experimental results show that the proposed scheme effectively reduces the positioning error.

关键词： Inertial navigation filtering algorithms Robot sensing systems Robot localization Vectors Quadrupedal robots Kalman filters Reliability Ultra wideband technology Intelligent control

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Top-$L$ Most Influential Community Detection Over Social Networks

Top-$L$ Most Influential Community Detection Over Social Net...

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International Conference on Data Engineering

作者： Nan Zhang Yutong Ye Xiang Lian Mingsong Chen East China Normal University Shanghai China Kent State University Kent United States

ISBN: (数字)9798350317152

ISBN: (纸本)9798350317169

In many real-world applications such as social network analysis and online marketing/advertising, community detection is a fundamental task to identify communities (subgraphs) in social networks with high structural cohesiveness. While previous works focus on detecting communities alone, they do not consider the collective influences of users in these communities on other user nodes in social networks. Inspired by this, in this paper, we investigate the influence propagation from some seed communities and their influential effects that result in the influenced communities. We propose a novel problem, named Top-L most Influential Community DEtection ( $\text{Top}L$ -ICDE) over social networks, which aims to retrieve top- $L$ seed communities with the highest influences, having high structural cohesiveness, and containing user-specified query keywords. To efficiently tackle the $\text{Top}L$ -ICDE problem, we design effective pruning strategies to filter out false alarms of seed communities and propose an effective index mechanism to facilitate efficient Top- $L$ community retrieval. We develop an efficient $\text{Top}L$ -ICDE answering algorithm by traversing the index and applying our proposed pruning strategies. We also formulate and tackle a variant of $\text{Top}L$ -ICDE, named diversified top-L most influential community detection ( $\text{Top}L$ -ICDE), which returns a set of $L$ diversified communities with the highest diversity score (i.e., collaborative influences by $L$ communities). We prove that $\text{DTop}L$ -ICDE is NP-hard, and propose an efficient greedy algorithm with our designed diversity score pruning. Through extensive experiments, we verify the efficiency and effectiveness of our proposed $\text{Top}L$ -ICDE and $\text{DTop}L$ -ICDE approaches over real/synthetic social networks under various parameter settings.

关键词： Greedy algorithms Social networking (online) Collaboration filtering algorithms Data engineering Indexes Cultural differences

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