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Tilt Measurement Method of Wooden Columns in Traditional Timber Buildings Based on Adaptive RANSAC and PCA Method 认领 引用
1
作者 Minyan Zhan Wei Yang +2 位作者 Minghao Wu Hsin-Yi Wang Yu-Hsien Ho 《Structural Durability & Health Monitoring》 EI 2026年第3期395-414,共20页
The inclination of wooden columns is a key indicator for evaluating the structural safety of traditional timber buildings in China.However,accurate measurement is challenging because these columns typically exhibit na... The inclination of wooden columns is a key indicator for evaluating the structural safety of traditional timber buildings in China.However,accurate measurement is challenging because these columns typically exhibit natural tapering,with diameters decreasing from the base to the top,and surface irregularities such as artificial cuts,cracks,and knots.Both the intrinsic geometric characteristics and surface defects reduce the precision of coordinate acquisition and the reliability of inclination estimation.To overcome these limitations,this study proposes a novel inclination measurement method for wooden columns in traditional timber buildings based on multi-section measurement and spatial line fitting.An adaptive random sample consensus algorithm is employed to effectively remove outliers induced by surface damage and measurement noise.Subsequently,principal component analysis is used to fit a three-dimensional spatial line through the center points of multiple cross-sections,enabling accurate computation of the inclination angle while accounting for structural imperfections.Moreover,the effects of damage defects,the number of measuring points,the measurement range,and the number of selected cross-sections on measurement accuracy are systematically investigated through statistical analysis,and corresponding recommended values for engineering practice are provided.The proposed method offers an efficient and reliable solution for inclination measurement,supporting the inspection and structural safety assessment of traditional timber columns. 展开更多
关键词 Traditional timber building inclination measurement of wooden column adaptive random sample consensus algorithm principal component analysis
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An Adaptive Trajectory-Assisted Dynamic Indoor Positioning Method Based on RSS Fingerprinting 认领 引用
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作者 Jing Liu Weijie Tan 《Computers, Materials & Continua》 SCIE EI 2026年第9期253-277,共25页
Due to its low hardware cost and ease of deployment,WiFi fingerprinting has become a prominent research direction in indoor positioning.However,traditional methods based on Received Signal Strength(RSS)still face thre... Due to its low hardware cost and ease of deployment,WiFi fingerprinting has become a prominent research direction in indoor positioning.However,traditional methods based on Received Signal Strength(RSS)still face three critical challenges:susceptibility to noise interference,lowretrieval efficiency as fingerprint databases scale up,and trajectory instability in dynamic environments.These challenges are inherently rooted in the stochastic fluctuation of RSS signals,the high-dimensional and non-Euclidean nature of fingerprint space,and the unpredictability of user movement patterns.To address these limitations,an adaptive trajectory-assisted dynamic indoor positioning algorithm based on RSS fingerprinting,termed AT-WKNN(Adaptive Trajectory-assisted Weighted K-Nearest Neighbor),is proposed.Specifically,a hybrid distance metric incorporating adaptive distance constraints is first designed to identify high-quality neighboring fingerprints while filtering out noisy samples,thereby improving positioning accuracy.Subsequently,aHierarchicalNavigable Small-World(HNSW)structure is employed to enable efficient fingerprint retrieval.In addition,a Kalman filter is utilized to smooth trajectory estimation and suppress dynamic noise.Experimental results demonstrate that the proposed AT-WKNN algorithm achieves a 43.0%improvement in positioning accuracy and a 6.90×increase in retrieval efficiency compared with the baseline WKNN method.Furthermore,validation on the large-scale UJIIndoorLoc benchmark dataset confirms the scalability and generalization capability of the proposed method. 展开更多
关键词 Indoor localization WiFi fingerprinting adaptive localization algorithm trajectory tracking
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Dynamic Multi-Objective Gannet Optimization(DMGO):An Adaptive Algorithm for Efficient Data Replication in Cloud Systems 认领 引用
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作者 P.William Ved Prakash Mishra +3 位作者 Osamah Ibrahim Khalaf Arvind Mukundan Yogeesh N Riya Karmakar 《Computers, Materials & Continua》 SCIE EI 2025年第9期5133-5156,共24页
Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple dat... Cloud computing has become an essential technology for the management and processing of large datasets,offering scalability,high availability,and fault tolerance.However,optimizing data replication across multiple data centers poses a significant challenge,especially when balancing opposing goals such as latency,storage costs,energy consumption,and network efficiency.This study introduces a novel Dynamic Optimization Algorithm called Dynamic Multi-Objective Gannet Optimization(DMGO),designed to enhance data replication efficiency in cloud environments.Unlike traditional static replication systems,DMGO adapts dynamically to variations in network conditions,system demand,and resource availability.The approach utilizes multi-objective optimization approaches to efficiently balance data access latency,storage efficiency,and operational costs.DMGO consistently evaluates data center performance and adjusts replication algorithms in real time to guarantee optimal system efficiency.Experimental evaluations conducted in a simulated cloud environment demonstrate that DMGO significantly outperforms conventional static algorithms,achieving faster data access,lower storage overhead,reduced energy consumption,and improved scalability.The proposed methodology offers a robust and adaptable solution for modern cloud systems,ensuring efficient resource consumption while maintaining high performance. 展开更多
关键词 Cloud computing data replication dynamic optimization multi-objective optimization gannet optimization algorithm adaptive algorithms resource efficiency scalability latency reduction energy-efficient computing
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An Adaptive Hybrid Metaheuristic for Solving the Vehicle Routing Problem with Time Windows under Uncertainty 认领 引用
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作者 Manuel J.C.S.Reis 《Computers, Materials & Continua》 SCIE EI 2025年第11期3023-3039,共17页
The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic ... The Vehicle Routing Problem with Time Windows(VRPTW)presents a significant challenge in combinatorial optimization,especially under real-world uncertainties such as variable travel times,service durations,and dynamic customer demands.These uncertainties make traditional deterministic models inadequate,often leading to suboptimal or infeasible solutions.To address these challenges,this work proposes an adaptive hybrid metaheuristic that integrates Genetic Algorithms(GA)with Local Search(LS),while incorporating stochastic uncertainty modeling through probabilistic travel times.The proposed algorithm dynamically adjusts parameters—such as mutation rate and local search probability—based on real-time search performance.This adaptivity enhances the algorithm’s ability to balance exploration and exploitation during the optimization process.Travel time uncertainties are modeled using Gaussian noise,and solution robustness is evaluated through scenario-based simulations.We test our method on a set of benchmark problems from Solomon’s instance suite,comparing its performance under deterministic and stochastic conditions.Results show that the proposed hybrid approach achieves up to a 9%reduction in expected total travel time and a 40% reduction in time window violations compared to baseline methods,including classical GA and non-adaptive hybrids.Additionally,the algorithm demonstrates strong robustness,with lower solution variance across uncertainty scenarios,and converges faster than competing approaches.These findings highlight the method’s suitability for practical logistics applications such as last-mile delivery and real-time transportation planning,where uncertainty and service-level constraints are critical.The flexibility and effectiveness of the proposed framework make it a promising candidate for deployment in dynamic,uncertainty-aware supply chain environments. 展开更多
关键词 Vehicle routing problem with time windows(VRPTW) hybrid metaheuristic genetic algorithm local search uncertainty modeling stochastic optimization adaptive algorithms combinatorial optimization transportation and logistics robust scheduling
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Adaptive Algorithms of Nonlinear Approximation with Finite Terms 认领 引用 被引量：7
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作者 Wen Bin WEI Yue Sheng XU Pei Xin YE 《Acta Mathematica Sinica,English Series》 SCIE 2007年第9期1663-1672,共10页
This paper deals with realizable adaptive algorithms of the nonlinear approximation with finite terms based on wavelets. We present a concrete algorithm by which we may find the required index set Am for the greedy al... This paper deals with realizable adaptive algorithms of the nonlinear approximation with finite terms based on wavelets. We present a concrete algorithm by which we may find the required index set Am for the greedy algorithm Gm^P（., Ψ）. This makes the greedy algorithm realize the near best approximation in practice. Moreover, we study the efficiency of the finite-term approximation of another Mgorithm introduced by Birge and Massart. 展开更多
关键词 nonlinear approximation dictionary Haar system adaptive algorithm near best approximation
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Adaptive block greedy algorithms for receiving multi-narrowband signal in compressive sensing radar reconnaissance receiver 认领 引用
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作者 ZHANG Chaozhu XU Hongyi JIANG Haiqing 《Journal of Systems Engineering and Electronics》 SCIE CSCD 2018年第6期1158-1169,共12页
This paper extends the application of compressive sensing(CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, ... This paper extends the application of compressive sensing(CS) to the radar reconnaissance receiver for receiving the multi-narrowband signal. By combining the concept of the block sparsity, the self-adaption methods, the binary tree search,and the residual monitoring mechanism, two adaptive block greedy algorithms are proposed to achieve a high probability adaptive reconstruction. The use of the block sparsity can greatly improve the efficiency of the support selection and reduce the lower boundary of the sub-sampling rate. Furthermore, the addition of binary tree search and monitoring mechanism with two different supports self-adaption methods overcome the instability caused by the fixed block length while optimizing the recovery of the unknown signal.The simulations and analysis of the adaptive reconstruction ability and theoretical computational complexity are given. Also, we verify the feasibility and effectiveness of the two algorithms by the experiments of receiving multi-narrowband signals on an analogto-information converter(AIC). Finally, an optimum reconstruction characteristic of two algorithms is found to facilitate efficient reception in practical applications. 展开更多
关键词 compressive sensing(CS) adaptive greedy algorithm block sparsity analog-to-information convertor(AIC) multinarrowband signal
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The Algorithms of Adaptive Active Noise Control Systems in a Duct 认领 引用
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作者 韩秀苓 程凡 +1 位作者 高建林 李传光 《Journal of Beijing Institute of Technology》 EI CAS 1995年第1期85+80-85,共86页
On the basis of the theory of adaptive active noise control(AANC) in a duct, this article discusses the algorithms of the adaptive control, compares the algorithm characteristics using LMS, RLS and LSL algorithms in t... On the basis of the theory of adaptive active noise control(AANC) in a duct, this article discusses the algorithms of the adaptive control, compares the algorithm characteristics using LMS, RLS and LSL algorithms in the adaptive filter in the AANC system, derives the recursive formulas of LMS algorithm. and obtains the LMS algorithm in computer simulation using FIR and IIR filters in AANC system. By means of simulation, we compare the attenuation levels with various input signals in AANC system and discuss the effects of step factor, order of filters and sound delay on the algorithm's convergence rate and attenuation level.We also discuss the attenuation levels with sound feedback using are and IIR filters in AANC system. 展开更多
关键词 adaptive control system adaptive filters noise control /adaptive algorithm LMS algorithm
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Novel adaptive IMEX two-step Runge-Kutta temporal discretization methods for unsteady flows 认领 引用
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作者 Xueyu QIN Jian YU +2 位作者 Xin ZHANG Zhenhua JIANG Chao YAN 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2025年第8期142-153,共12页
Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of un... Efficient and accurate simulation of unsteady flow presents a significant challenge that needs to be overcome in computational fluid dynamics.Temporal discretization method plays a crucial role in the simulation of unsteady flows.To enhance computational efficiency,we propose the Implicit-Explicit Two-Step Runge-Kutta(IMEX-TSRK)time-stepping discretization methods for unsteady flows,and develop a novel adaptive algorithm that correctly partitions spatial regions to apply implicit or explicit methods.The novel adaptive IMEX-TSRK schemes effectively handle the numerical stiffness of the small grid size and improve computational efficiency.Compared to implicit and explicit Runge-Kutta(RK)schemes,the IMEX-TSRK methods achieve the same order of accuracy with fewer first derivative calculations.Numerical case tests demonstrate that the IMEX-TSRK methods maintain numerical stability while enhancing computational efficiency.Specifically,in high Reynolds number flows,the computational efficiency of the IMEX-TSRK methods surpasses that of explicit RK schemes by more than one order of magnitude,and that of implicit RK schemes several times over. 展开更多
关键词 Implicit-explicit temporal methods Two-step Runge-Kutta methods Adaptive algorithm Unsteady flows Navier-Stokes equations
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Effect of Tooth Geometry on Multi-cycle Meshing Temperature of POM Worm Gears:Parametric Study via an Adaptive Iteration Algorithm 认领 引用
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作者 Kaixing Li Wujiao Xu +1 位作者 Yonggang Liu Datong Qin 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2025年第2期427-439,共13页
Meshing temperature analyses of polymer gears reported in the literature mainly concern the effects of various material combinations and loading conditions,as their impacts could be seen in the first few meshing cycle... Meshing temperature analyses of polymer gears reported in the literature mainly concern the effects of various material combinations and loading conditions,as their impacts could be seen in the first few meshing cycles.However,the effects of tooth geometry parameters could manifest as the meshing cycles increase.This study investigated the effects of tooth geometry parameters on the multi-cycle meshing temperature of polyoxymethylene(POM)worm gears,aiming to control the meshing temperature elevation by tuning the tooth geometry.Firstly,a finite element(FE)model capable of separately calculating the heat generation and simulating the heat propagation was established.Moreover,an adaptive iteration algorithm was proposed within the FE framework to capture the influence of the heat generation variation from cycle to cycle.This algorithm proved to be feasible and highly efficient compared with experimental results from the literature and simulated results via the full-iteration algorithm.Multi-cycle meshing temperature analyses were conducted on a series of POM worm gears with different tooth geometry parameters.The results reveal that,within the range of 14.5°to 25°,a pressure angle of 25°is favorable for reducing the peak surface temperature and overall body temperature of POM worm gears,which influence flank wear and load-carrying capability,respectively.However,addendum modification should be weighed because it helps with load bearing but increases the risk of severe flank wear.This paper proposes an efficient iteration algorithm for multi-cycle meshing temperature analysis of polymer gears and proves the feasibility of controlling the meshing temperature elevation during multiple cycles by tuning tooth geometry. 展开更多
关键词 POM worm gears Multi-cycle meshing temperature Adaptive iteration algorithm Tooth geometry parameters Parametric study
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Kinematic Calibration of a 5-DoF Parallel Machining Robot with a Novel Adaptive and Weighted Identification Method Based on Generalized Cross Validation 认领 引用
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作者 Lefeng Gu Fugui Xie 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2025年第2期262-278,共17页
Accurate kinematic calibration is the very foundation for robots'application in industry demanding high precision such as machining.Considering the complex error characteristic and severe ill-posed identification ... Accurate kinematic calibration is the very foundation for robots'application in industry demanding high precision such as machining.Considering the complex error characteristic and severe ill-posed identification issues of a 5-DoF parallel machining robot,this paper proposes an adaptive and weighted identification method to achieve high-precision kinematic calibration while maintaining reliable stability.First,a kinematic error propagation mechanism model considering the non-ideal constraints and the screw self-rotation is formulated by incorporating the intricate structure of multiple chains and a unique driven screw arrangement of the robot.To address the challenge of accurately identifying such a sophisticated error model,a novel adaptive and weighted identification method based on generalized cross validation(GCV)is proposed.Specifically,this approach innovatively introduces Gauss-Markov estimation into the GCV algorithm and utilizes prior physical information to construct both a weighted identification model and a weighted cross-validation function,thus eliminating the inaccuracy caused by significant differences in dimensional magnitudes of pose errors and achieving accurate identification with flexible numerical stability.Finally,the kinematic calibration experiment is conducted.The comparative experimental results demonstrate that the presented approach is effective and has enhanced accuracy performance over typical least squares methods,with maximum position and orientation errors reduced from 2.279 mm to 0.028 mm and from 0.206°to 0.017°,respectively. 展开更多
关键词 Parallel machining robot Accurate kinematic calibration Weighted identification model Adaptive identification algorithm
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Variable Projection Order Adaptive Filtering Algorithm for Self-interference Cancellation in Airborne Radars 认领 引用
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作者 LI Haorui GAO Ying +1 位作者 GUO Xinyu OU Shifeng 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2025年第4期497-508,共12页
The adaptive filtering algorithm with a fixed projection order is unable to adjust its performance in response to changes in the external environment of airborne radars.To overcome this limitation,a new approach is in... The adaptive filtering algorithm with a fixed projection order is unable to adjust its performance in response to changes in the external environment of airborne radars.To overcome this limitation,a new approach is introduced,which is the variable projection order Ekblom norm-promoted adaptive algorithm(VPO-EPAA).The method begins by examining the mean squared deviation(MSD)of the EPAA,deriving a formula for its MSD.Next,it compares the MSD of EPAA at two different projection orders and selects the one that minimizes the MSD as the parameter for the current iteration.Furthermore,the algorithm’s computational complexity is analyzed theoretically.Simulation results from system identification and self-interference cancellation show that the proposed algorithm performs exceptionally well in airborne radar signal self-interference cancellation,even under various noise intensities and types of interference. 展开更多
关键词 adaptive filtering algorithm airborne radar variable projection order mean squared deviation self-interference cancellation
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Novel algorithm of traffic signals adaptive control on urban roads intersections 认领 引用 被引量：1
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作者 Huanjiong Zhang 《Journal of Highway and Transportation Research and Development(English Edition)》 2025年第1期25-28,共4页
The control of traffic flows on urban roads intersections through the traffic control signals is very important,not only does the jammed traffic statement valuably relieve and the ratio of the traffic availability inc... The control of traffic flows on urban roads intersections through the traffic control signals is very important,not only does the jammed traffic statement valuably relieve and the ratio of the traffic availability increase,but also the traffic accidents evidently decrease.In this paper,an adaptive algorithm of traffic control signals on the urban roads intersections is designed in,this new algorithm can actively adjust the concrete control times of the traffic control signals based on the perceiving information of the waiting vehicles in real time,then the dynamic balance between the traffic control signals and the traffic flows can be realized.Furthermore,through experiment testing and demonstrating,this adaptive algorithm expresses some fine performances,it also shows good application prospect in the field of smart city. 展开更多
关键词 Traffic engineering Urban road intersections Traffic control signals Perception devices Adaptive algorithm Control phases
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CAGE-YOLO:A Dense Small Object Detection Model for Aquaculture Net Cages Based on Remote Sensing Images 认领 引用 被引量：1
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作者 ZHANG Wenbo JIANG Yijue +2 位作者 SONG Wei HE Qi ZHANG Wenbo 《智慧农业（中英文）》 CSCD 2026年第2期98-117,共20页
[Objective]Detecting dense and small aquaculture net cages in complex backgrounds is difficult,the purpose of this study is to build a specialized dataset and design a targeted detection model that enhances recognitio... [Objective]Detecting dense and small aquaculture net cages in complex backgrounds is difficult,the purpose of this study is to build a specialized dataset and design a targeted detection model that enhances recognition accuracy and robustness for practical aquaculture management.[Methods]A dataset of aquaculture net cages was constructed using highresolution remote sensing imagery collected from seven representative farming regions(Australia,Canada,Chile,Croatia,Greece,China,and the Faroe Islands),and Cage-YOLO,a deep learning model based on YOLOv5,was proposed for detecting dense and small aquaculture net cages.First,an adaptive dense perception algorithm was introduced,which automatically selects and generates feature maps that reflect the high-density distribution of small aquaculture net cages.Second,an enhanced module based on spatial pyramid pooling fast was integrated to effectively reduce background noise interference and improve global feature extraction capabilities.Finally,a mixed attention block was incorporated to further enhance the model's perception of dense and small objects.[Results and Discussions]Experimental results showed that the proposed Cage-YOLO achieved improvements over the original YOLOv5 in terms of precision,recall,and mean average precision by 5.6,21.8,and 17.4 percentage points,respectively.The model size was maintained at 16.9 MB,demonstrating both strong performance and deployment advantages.[Conclusions]This study provides a new approach for dense and small object detection and offers technical support for the intelligent management of marine cage aquaculture. 展开更多
关键词 aquaculture net cage small object detection adaptive dense perception algorithm enhancement spatial pyramid pooling mix attention block
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Adaptive Robust Control for a Class of Uncertain MIMO Non-affine Nonlinear Systems 认领 引用 被引量：9
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作者 Longsheng Chen Qi Wang 《IEEE/CAA Journal of Automatica Sinica》 EI 2016年第1期105-112,共8页
In this paper, the adaptive robust tracking control scheme is proposed for a class of multi-input and multi-output (MIMO) non-affine systems with uncertain structure and parameters, unknown control direction and unkno... In this paper, the adaptive robust tracking control scheme is proposed for a class of multi-input and multi-output (MIMO) non-affine systems with uncertain structure and parameters, unknown control direction and unknown external disturbance based on backstepping technique. The MIMO non-affine system is first transformed into a time-varying system with strict feedback structure using the mean value theorem, and then the bounded time-varying parameters are estimated by adaptive algorithms with projection. To handle the possible 'controller singularity' problem caused by unknown control direction, a Nussbaum function is employed, and the dynamic surface control (DSC) method is applied to solve the problem of 'explosion of complexity' in backstepping control. It is proved that the proposed control scheme can guarantee that all signals of the closed-loop system are bounded through Lyapunov stability theorem and decoupled backstepping method. Simulation results are presented to illustrate the effectiveness of the proposed control scheme. © 2014 Chinese Association of Automation. 展开更多
关键词 Adaptive algorithms Backstepping Closed loop control systems Closed loop systems Functions Nonlinear systems Robust control Time varying systems Uncertainty analysis
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NURBS CURVE INTERPOLATOR WITH ADAPTIVE ACCELERATION-DECELERATION CONTROL 认领 引用 被引量：3
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作者 刘凯 赵东标 陆永华 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2008年第4期241-247,共7页
The feedrate profile of non-uniform rational B-spline （NURBS） interpolation due to the contour errors is analyzed. A NURBS curve interpolator with adaptive acceleration-deceleration control is presented. In interpo-... The feedrate profile of non-uniform rational B-spline （NURBS） interpolation due to the contour errors is analyzed. A NURBS curve interpolator with adaptive acceleration-deceleration control is presented. In interpo- lation preprocessing, the sensitive zones of feedrate variations are processed with acceleration-deceleration control. By using the proposed algorithm, the machining accuracy is guaranteed and the feedrate is adaptively adjusted to he smoothed. The mechanical shock imposed in the servo system is avoided by the first and the second time derivatives of feedrates. A simulation of NURBS interpolation is given to demonstrate the validity and the effectiveness of the algorithm. The proposed interpolator can also be applied to the trajectory planning of the other parametric curves. 展开更多
关键词 numerical control systems interpolation adaptive algorithms NURBS curve interpolator adaptive acceleration and deceleration limited jerk
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Weighted adaptive filtering algorithm for carrier tracking of deep space signal 认领 引用 被引量：9
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作者 Song Qingping Liu Rongke 《Chinese Journal of Aeronautics》 SCIE EI CAS CSCD 2015年第4期1236-1244,共9页
Carrier tracking is laid great emphasis and is the difficulty of signal processing in deep space communication system.For the autonomous radio receiving system in deep space, the tracking of the received signal is aut... Carrier tracking is laid great emphasis and is the difficulty of signal processing in deep space communication system.For the autonomous radio receiving system in deep space, the tracking of the received signal is automatic when the signal to noise ratio（SNR） is unknown.If the frequency-locked loop（FLL） or the phase-locked loop（PLL） with fixed loop bandwidth, or Kalman filter with fixed noise variance is adopted, the accretion of estimation error and filter divergence may be caused.Therefore, the Kalman filter algorithm with adaptive capability is adopted to suppress filter divergence.Through analyzing the inadequacies of Sage–Husa adaptive filtering algorithm, this paper introduces a weighted adaptive filtering algorithm for autonomous radio.The introduced algorithm may resolve the defect of Sage–Husa adaptive filtering algorithm that the noise covariance matrix is negative definite in filtering process.In addition, the upper diagonal（UD） factorization and innovation adaptive control are used to reduce model estimation errors,suppress filter divergence and improve filtering accuracy.The simulation results indicate that compared with the Sage–Husa adaptive filtering algorithm, this algorithm has better capability to adapt to the loop, convergence performance and tracking accuracy, which contributes to the effective and accurate carrier tracking in low SNR environment, showing a better application prospect. 展开更多
关键词 Adaptive algorithms Carrier tracking Deep space communicationKalman filters Tracking accuracy Weighted
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Parallel implementation and optimization of LMS adaptive filtering algorithms based on vector DSP 认领 引用
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作者 Yonghua Hu Linyun Deng +1 位作者 Xiangyu Gao Zhezhuo Zhao 《CCF Transactions on High Performance Computing》 EI CSCD 2026年第2期180-195,共16页
The Least Mean Square(LMS)adaptive filtering algorithm is a significant filtering algorithm widely used in noise processing and other fields that automatically adjusts the values of filter coefficients according to th... The Least Mean Square(LMS)adaptive filtering algorithm is a significant filtering algorithm widely used in noise processing and other fields that automatically adjusts the values of filter coefficients according to the results,aimed at optimizing the filtered results.Based on a basic serial LMS adaptive filtering algorithm,we propose a vectorized parallel processing scheme for the LMS adaptive filtering algorithm in this work.By combining the characteristics of the algorithm processing flow and those of the parallel technologies used in vector Digital Signal Processes(DSPs),the optimizations such as loop fusion,double-word accessing,and vector shuffling of the LMS algorithm are studied in depth,and the loop unrolling optimization method is used to accelerate the calculation of the algorithm further.Experimental research was conducted on the high-performance FT-M7002 DSP platform in this paper.The results show that,compared with the running performance of the LMS adaptive filtering algorithm in Texas Instruments(TI)’s dsplib library on the TMS320C6678 processor,the optimization effect of the proposed optimization algorithm in this paper can achieve a maximum speed-up ratio of up to 6.9×for medium-scale data.The merged memory access optimization implemented on the GPU platform achieves an average 1.5x speedup compared to the basic parallel scheme. 展开更多
关键词 Vector DSP High-performance computing Parallel optimization LMS adaptive filtering algorithm
LMAdam:Enhancing Adam via Linear Multistep Discretization 认领 引用
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作者 Liangming Chen Longbang Wang +1 位作者 Long Jin Jun Wang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2026年第1期161-169,共9页
In this paper,we propose a learning algorithm termed linear multistep adaptive moment(LMAdam) to enhance the adaptive moment(Adam) algorithm for machine learning.Considering Adam as a single-step discretization of its... In this paper,we propose a learning algorithm termed linear multistep adaptive moment(LMAdam) to enhance the adaptive moment(Adam) algorithm for machine learning.Considering Adam as a single-step discretization of its continuous counterpart,we develop the LMAdam algorithm based on a linear multistep discretization scheme.We design a feedforward neural network for learning the coefficients of the multistep terms with ensured consistency and select the coefficients to ensure zero stability of the multistep terms.We experimentally demonstrate the superiority of the LMAdam via extensive experimentation on benchmark datasets for training various deep neural networks in three applications. 展开更多
关键词 Adaptive moment(Adam)algorithm continuous dynamic deep learning multistep discretization
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FREQUENCY-DOMAIN IMPLEMENTATION OF FILTERED-X ALGORITHMS WITH ON-LINE SYSTEM IDENTIFICATION FOR VIBRATION CONTROL 认领 引用 被引量：2
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作者 陈卫东 顾仲权 《Transactions of Nanjing University of Aeronautics and Astronautics》 1995年第1期99-103,共5页
This paper describes the implementation of frequency-domain least mean squares (LMS) and Filtered-X algorithms and compares the performance of the frequencydomain adaptive control algorithm to a comparable timedomain ... This paper describes the implementation of frequency-domain least mean squares (LMS) and Filtered-X algorithms and compares the performance of the frequencydomain adaptive control algorithm to a comparable timedomain controller. When the frequency-domain LMS step size is allowed to vary as a function of frequency,the frequency-domain algorithm exhibits a better vibration reduction than the time-domain algorithm for the weaker frequencies in the energy spectrum. 展开更多
关键词 vibration reduction feedforward control adaptive filters vibration control adaptive algorithms
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Adaptive Signal Enhancement Unit for EEG Analysis in Remote Patient Care Monitoring Systems 认领 引用 被引量：1
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作者 Ch.Srinivas K.Chandrabhushana Rao 《Computers, Materials & Continua》 SCIE EI 2021年第5期1801-1817,共17页
In this paper we propose an efcient process of physiological artifact elimination methodology from brain waves(BW),which are also commonly known as electroencephalogram(EEG)signal.In a clinical environment during the ... In this paper we propose an efcient process of physiological artifact elimination methodology from brain waves(BW),which are also commonly known as electroencephalogram(EEG)signal.In a clinical environment during the acquisition of BW several artifacts contaminates the actual BW component.This leads to inaccurate and ambiguous diagnosis.As the statistical nature of the EEG signal is more non-stationery,adaptive ltering is the more promising method for the process of artifact elimination.In clinical conditions,the conventional adaptive techniques require many numbers of computational operations and leads to data samples overlapping and instability of the algorithm used.This causes delay in diagnosis and decision making.To overcome this problem in our work we propose to set a threshold value to diminish the problem of round off error.The resultant adaptive algorithm based on this strategy is Non-linear Least mean square(NL2MS)algorithm.Again,to improve this algorithm in terms of ltering capability we perform data normalization,using this algorithm several hybrid versions are developed to improve ltering and reduce computational operations.Using the method,a new signal enhancement unit(SEU)is realized and performance of various hybrid versions of algorithms examined using real EEG signals recorded from the subject.The ability of the proposed schemes is measured in terms of convergence,enhancement and multiplications required.Among various SEUs,the MCN2L 2MS algorithm achieves 14.6734,12.8732,10.9257,15.7790 dB during the artifact removal of RA,EMG,CSA and EBA components with only two multiplications.Hence,this algorithm seems to be better candidate for artifact elimination. 展开更多
关键词 Adaptive algorithms artifacts brain waves clipped algorithms signal enhancement unit wireless EEG monitoring
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