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Model-driven full system dynamics estimation of PMSM-driven chain shell magazine
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作者 Kai Wei Longmiao Chen Quan Zou 《Defence Technology(防务技术)》 SCIE EI CAS CSCD 2024年第9期147-156,共10页
Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is pro... Based on the system dynamic model, a full system dynamics estimation method is proposed for a chain shell magazine driven by a permanent magnet synchronous motor(PMSM). An adaptive extended state observer(AESO) is proposed to estimate the unmeasured states and disturbance, in which the model parameters are adjusted in real time. Theoretical analysis shows that the estimation errors of the disturbances and unmeasured states converge exponentially to zero, and the parameter estimation error can be obtained from the extended state. Then, based on the extended state of the AESO, a novel parameter estimation law is designed. Due to the convergence of AESO, the novel parameter estimation law is insensitive to controllers and excitation signal. Under persistent excitation(PE) condition, the estimated parameters will converge to a compact set around the actual parameter value. Without PE signal, the estimated parameters will converge to zero for the extended state. Simulation and experimental results show that the proposed method can accurately estimate the unmeasured states and disturbance of the chain shell magazine, and the estimated parameters will converge to the actual value without strictly continuous PE signals. 展开更多
关键词 Chain shell magazine Full system dynamics estimation Disturbance estimation Parameter estimation Adaptive extended state observer
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Target layer state estimation in multi-layer complex dynamical networks considering nonlinear node dynamics
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作者 吴亚勇 王欣伟 蒋国平 《Chinese Physics B》 SCIE EI CAS CSCD 2024年第4期245-252,共8页
In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation ... In many engineering networks, only a part of target state variables are required to be estimated.On the other hand,multi-layer complex network exists widely in practical situations.In this paper, the state estimation of target state variables in multi-layer complex dynamical networks with nonlinear node dynamics is studied.A suitable functional state observer is constructed with the limited measurement.The parameters of the designed functional observer are obtained from the algebraic method and the stability of the functional observer is proven by the Lyapunov theorem.Some necessary conditions that need to be satisfied for the design of the functional state observer are obtained.Different from previous studies, in the multi-layer complex dynamical network with nonlinear node dynamics, the proposed method can estimate the state of target variables on some layers directly instead of estimating all the individual states.Thus, it can greatly reduce the placement of observers and computational cost.Numerical simulations with the three-layer complex dynamical network composed of three-dimensional nonlinear dynamical nodes are developed to verify the effectiveness of the method. 展开更多
关键词 multi-layer complex dynamical network nonlinear node dynamics target state estimation functional state observer
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Set-Membership Filtering Approach to Dynamic Event-Triggered Fault Estimation for a Class of Nonlinear Time-Varying Complex Networks
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作者 Xiaoting Du Lei Zou Maiying Zhong 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第3期638-648,共11页
The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered ... The present study addresses the problem of fault estimation for a specific class of nonlinear time-varying complex networks,utilizing an unknown-input-observer approach within the framework of dynamic event-triggered mechanism(DETM).In order to optimize communication resource utilization,the DETM is employed to determine whether the current measurement data should be transmitted to the estimator or not.To guarantee a satisfactory estimation performance for the fault signal,an unknown-input-observer-based estimator is constructed to decouple the estimation error dynamics from the influence of fault signals.The aim of this paper is to find the suitable estimator parameters under the effects of DETM such that both the state estimates and fault estimates are confined within two sets of closed ellipsoid domains.The techniques of recursive matrix inequality are applied to derive sufficient conditions for the existence of the desired estimator,ensuring that the specified performance requirements are met under certain conditions.Then,the estimator gains are derived by minimizing the ellipsoid domain in the sense of trace and a recursive estimator parameter design algorithm is then provided.Finally,a numerical example is conducted to demonstrate the effectiveness of the designed estimator. 展开更多
关键词 dynamic event-triggered mechanism(DETM) fault estimation nonlinear time-varying complex networks set-member-ship filtering unknown input observer
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Improving the accuracy of precipitation estimates in a typical inland arid area of China using a dynamic Bayesian model averaging approach
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作者 XU Wenjie DING Jianli +2 位作者 BAO Qingling WANG Jinjie XU Kun 《Journal of Arid Land》 SCIE CSCD 2024年第3期331-354,共24页
Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating a... Xinjiang Uygur Autonomous Region is a typical inland arid area in China with a sparse and uneven distribution of meteorological stations,limited access to precipitation data,and significant water scarcity.Evaluating and integrating precipitation datasets from different sources to accurately characterize precipitation patterns has become a challenge to provide more accurate and alternative precipitation information for the region,which can even improve the performance of hydrological modelling.This study evaluated the applicability of widely used five satellite-based precipitation products(Climate Hazards Group InfraRed Precipitation with Station(CHIRPS),China Meteorological Forcing Dataset(CMFD),Climate Prediction Center morphing method(CMORPH),Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record(PERSIANN-CDR),and Tropical Rainfall Measuring Mission Multi-satellite Precipitation Analysis(TMPA))and a reanalysis precipitation dataset(ECMWF Reanalysis v5-Land Dataset(ERA5-Land))in Xinjiang using ground-based observational precipitation data from a limited number of meteorological stations.Based on this assessment,we proposed a framework that integrated different precipitation datasets with varying spatial resolutions using a dynamic Bayesian model averaging(DBMA)approach,the expectation-maximization method,and the ordinary Kriging interpolation method.The daily precipitation data merged using the DBMA approach exhibited distinct spatiotemporal variability,with an outstanding performance,as indicated by low root mean square error(RMSE=1.40 mm/d)and high Person's correlation coefficient(CC=0.67).Compared with the traditional simple model averaging(SMA)and individual product data,although the DBMA-fused precipitation data were slightly lower than the best precipitation product(CMFD),the overall performance of DBMA was more robust.The error analysis between DBMA-fused precipitation dataset and the more advanced Integrated Multi-satellite Retrievals for Global Precipitation Measurement Final(IMERG-F)precipitation product,as well as hydrological simulations in the Ebinur Lake Basin,further demonstrated the superior performance of DBMA-fused precipitation dataset in the entire Xinjiang region.The proposed framework for solving the fusion problem of multi-source precipitation data with different spatial resolutions is feasible for application in inland arid areas,and aids in obtaining more accurate regional hydrological information and improving regional water resources management capabilities and meteorological research in these regions. 展开更多
关键词 precipitation estimates satellite-based and reanalysis precipitation dynamic Bayesian model averaging streamflow simulation Ebinur Lake Basin XINJIANG
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MOVING OBJECT TRACKING IN DYNAMIC IMAGE SEQUENCE BASED ON ESTIMATION OF MOTION VECTORS OF FEATURE POINTS 被引量:2
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作者 黎宁 周建江 张星星 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI 2009年第4期295-300,共6页
An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change (MIC) algor... An improved estimation of motion vectors of feature points is proposed for tracking moving objects of dynamic image sequence. Feature points are firstly extracted by the improved minimum intensity change (MIC) algorithm. The matching points of these feature points are then determined by adaptive rood pattern searching. Based on the random sample consensus (RANSAC) method, the background motion is finally compensated by the parameters of an affine transform of the background motion. With reasonable morphological filtering, the moving objects are completely extracted from the background, and then tracked accurately. Experimental results show that the improved method is successful on the motion background compensation and offers great promise in tracking moving objects of the dynamic image sequence. 展开更多
关键词 motion compensation motion estimation feature extraction moving object tracking dynamic image sequence
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Time-Lapse Full-Waveform Inversion Using Cross-Correlation-Based Dynamic Time Warping
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作者 Jianhua Wang Qingping Li +1 位作者 Shouwei Zhou Yufa He 《哈尔滨工程大学学报(英文版)》 CSCD 2024年第3期634-644,共11页
Offshore carbon capture, utilization, and storage(OCCUS) is regarded as a crucial technology for mitigating greenhouse gas emissions.Quantitative monitoring maps of sealed carbon dioxide are necessary in a comprehensi... Offshore carbon capture, utilization, and storage(OCCUS) is regarded as a crucial technology for mitigating greenhouse gas emissions.Quantitative monitoring maps of sealed carbon dioxide are necessary in a comprehensive OCCUS project. A potential high-resolution method for the aforementioned purpose lies in the full-waveform inversion(FWI) of time-lapse seismic data. However, practical applications of FWI are severely restricted by the well-known cycle-skipping problem. A new time-lapse FWI method using cross-correlation-based dynamic time warping(CDTW) is proposed to detect changes in the subsurface property due to carbon dioxide(CO_(2)) injection and address the aforementioned issue. The proposed method, namely CDTW, which combines the advantages of cross-correlation and dynamic time warping, is employed in the automatic estimation of the discrepancy between the seismic signals simulated using the baseline/initial model and those acquired. The proposed FWI method can then back-project the estimated discrepancy to the subsurface space domain, thereby facilitating retrieval of the induced subsurface property change by taking the difference between the inverted baseline and monitor models. Numerical results on pairs of signals prove that CDTW can obtain reliable shifts under amplitude modulation and noise contamination conditions. The performance of CDTW substantially outperforms that of the conventional dynamic time warping method. The proposed time-lapse fullwaveform inversion(FWI) method is applied to the Frio-2 CO_(2) storage model. The baseline and monitor models are inverted from the corresponding time-lapse seismic data. The changes in velocity due to CO_(2) injection are reconstructed by the difference between the baseline and the monitor models. 展开更多
关键词 Full-waveform inversion dynamic time warping Ocean carbon dioxide storage monitoring Discrepancy estimation Model test
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Vehicle Dynamic State Estimation: State of the Art Schemes and Perspectives 被引量:12
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作者 Hongyan Guo Dongpu Cao +3 位作者 Hong Chen Chen Lv Huaji Wang Siqi Yang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2018年第2期418-431,共14页
Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developmen... Next-generation vehicle control and future autonomous driving require further advances in vehicle dynamic state estimation. This article provides a concise review, along with the perspectives, of the recent developments in the estimation of vehicle dynamic states. The definitions used in vehicle dynamic state estimation are first introduced, and alternative estimation structures are presented. Then, the sensor configuration schemes used to estimate vehicle velocity, sideslip angle, yaw rate and roll angle are presented. The vehicle models used for vehicle dynamic state estimation are further summarized, and representative estimation approaches are discussed. Future concerns and perspectives for vehicle dynamic state estimation are also discussed. 展开更多
关键词 Index Terms-estimation structure extended Kalman filter sensor configuration sideslip angle estimation vehicle dynamicstate estimation vehicle dynamics model.
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Coupled dynamic model of state estimation for hypersonic glide vehicle 被引量:13
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作者 ZHANG Kai XIONG Jiajun FU Tingting 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2018年第6期1284-1292,共9页
Aiming at handling complicated maneuvers or other unpredicted emergencies for hypersonic glide vehicle tracking,three coupled dynamic models of state estimation based on the priori information between guidance variabl... Aiming at handling complicated maneuvers or other unpredicted emergencies for hypersonic glide vehicle tracking,three coupled dynamic models of state estimation based on the priori information between guidance variables and aerodynamics are presented. Firstly, the aerodynamic acceleration acting on the target is analyzed to reveal the essence of the target’s motion.Then three coupled structures for modeling aerodynamic parameters are developed by different ideas: the spiral model with a harmonic oscillator, the bank model with trigonometric functions of the bank angle and the guide model with the changing rule of guidance variables. Meanwhile, the comparison discussion is concluded to show the novelty and advantage of these models.Finally, a performance assessment in different simulation cases is presented and detailed analysis is revealed. The results show that the proposed models perform excellent properties. Moreover, the guide model produces the best tracking performance and the bank model shows the second; however, the spiral model does not outperform the maneuvering reentry vehicle(MaRV) model markedly. 展开更多
关键词 hypersonic glide vehicle state estimation dynamic model aerodynamic parameter guidance variable
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Dynamic threshold for SPWVD parameter estimation based on Otsu algorithm 被引量:10
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作者 Ning Ma Jianxin Wang 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2013年第6期919-924,共6页
Time-frequency-based methods are proven to be effective for parameter estimation of linear frequency modulation (LFM) signals. The smoothed pseudo Winger-Ville distribution (SPWVD) is used for the parameter estima... Time-frequency-based methods are proven to be effective for parameter estimation of linear frequency modulation (LFM) signals. The smoothed pseudo Winger-Ville distribution (SPWVD) is used for the parameter estimation of multi-LFM signals, and a method of the SPWVD binarization by a dynamic threshold based on the Otsu algorithm is proposed. The proposed method is effective in the demand for the estimation of different parameters and the unknown signal-to-noise ratio (SNR) circumstance. The performance of this method is confirmed by numerical simulation. 展开更多
关键词 parameter estimation smoothed pseudo Winger-Ville distribution (SPWVD) dynamic threshold Otsu algorithm
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Influence of Tire Dynamics on Slip Ratio Estimation of Independent Driving Wheel System 被引量:4
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作者 LI Jianqiu SONG Ziyou +1 位作者 WEI Yintao OUYANG Minggao 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2014年第6期1203-1210,共8页
The independent driving wheel system, which is composed of in-wheel permanent magnet synchronous motor(I-PMSM) and tire, is more convenient to estimate the slip ratio because the rotary speed of the rotor can be acc... The independent driving wheel system, which is composed of in-wheel permanent magnet synchronous motor(I-PMSM) and tire, is more convenient to estimate the slip ratio because the rotary speed of the rotor can be accurately measured. However, the ring speed of the tire ring doesn’t equal to the rotor speed considering the tire deformation. For this reason, a deformable tire and a detailed I-PMSM are modeled by using Matlab/Simulink. Moreover, the tire/road contact interface(a slippery road) is accurately described by the non-linear relaxation length-based model and the Magic Formula pragmatic model. Based on the relatively accurate model, the error of slip ratio estimated by the rotor rotary speed is analyzed in both time and frequency domains when a quarter car is started by the I-PMSM with a definite target torque input curve. In addition, the natural frequencies(NFs) of the driving wheel system with variable parameters are illustrated to present the relationship between the slip ratio estimation error and the NF. According to this relationship, a low-pass filter, whose cut-off frequency corresponds to the NF, is proposed to eliminate the error in the estimated slip ratio. The analysis, concerning the effect of the driving wheel parameters and road conditions on slip ratio estimation, shows that the peak estimation error can be reduced up to 75% when the LPF is adopted. The robustness and effectiveness of the LPF are therefore validated. This paper builds up the deformable tire model and the detailed I-PMSM models, and analyzes the effect of the driving wheel parameters and road conditions on slip ratio estimation. 展开更多
关键词 electric vehicle (EV) driving wheel system tire dynamics slip ratio estimation characteristic frequency low-pass filter (LPF)
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Consensus Control of Multi-Agent Systems Using Fault-Estimation-in-the-Loop:Dynamic Event-Triggered Case 被引量:21
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作者 Yamei Ju Derui Ding +2 位作者 Xiao He Qing-Long Han Guoliang Wei 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2022年第8期1440-1451,共12页
The paper develops a novel framework of consensus control with fault-estimation-in-the-loop for multi-agent systems(MASs)in the presence of faults.A dynamic event-triggered protocol(DETP)by adding an auxiliary variabl... The paper develops a novel framework of consensus control with fault-estimation-in-the-loop for multi-agent systems(MASs)in the presence of faults.A dynamic event-triggered protocol(DETP)by adding an auxiliary variable is utilized to improve the utilization of communication resources.First,a novel estimator with a noise bias is put forward to estimate the existed fault and then a consensus controller with fault compensation(FC)is adopted to realize the demand of reliability and safety of addressed MASs.Subsequently,a novel consensus control framework with fault-estimation-in-the-loop is developed to achieve the predetermined consensus performance with the l_(2)-l_(∞)constraint by employing the variance analysis and the Lyapunov stability approaches.Furthermore,the desired estimator and controller gains are obtained in light of the solution to an algebraic matrix equation and a linear matrix inequality in a recursive way,respectively.Finally,a simulation result is employed to verify the usefulness of the proposed design framework. 展开更多
关键词 Consensus control dynamic event-triggered protocol(DETP) fault compensation(FC) fault estimation multi-agent systems(MASs)
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Ultrasonic attenuation estimation based on time-frequency analysis 被引量:3
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作者 Gao Feng Wei Jian-Xin Di Bang-Rang 《Applied Geophysics》 SCIE CSCD 2019年第4期414-426,559,共14页
The quality factor(or Q value)is an important parameter for characterizing the inelastic properties of rock.Achieving a Q value estimation with high accuracy and stability is still challenging.In this study,a new meth... The quality factor(or Q value)is an important parameter for characterizing the inelastic properties of rock.Achieving a Q value estimation with high accuracy and stability is still challenging.In this study,a new method for estimating ultrasonic attenuation using a spectral ratio based on an S transform(SR-ST)is presented to improve the stability and accuracy of Q estimation.The variable window of ST is used to solve the time window problem.We add two window factors to the Gaussian window function in the ST.The window factors can adjust the scale of the Gaussian window function to the ultrasonic signal,which reduces the calculation error attributed to the conventional Gaussian window function.Meanwhile,the frequency bandwidth selection rules for the linear regression of the amplitude ratio are given to further improve stability and accuracy.First,the feasibility and influencing factors of the SR-ST method are studied through numerical testing and standard sample experiments.Second,artificial samples with different Q values are used to study the adaptability and stability of the SR-ST method.Finally,a further comparison between the new method and the conventional spectral ratio method(SR)is conducted using rock field samples,again addressing stability and accuracy.The experimental results show that this method will yield an error of approximately 36%using the conventional Gaussian window function.This problem can be solved by adding the time window factors to the Gaussian window function.The frequency bandwidth selection rules and mean slope value of the amplitude ratio used in the SR-ST method can ensure that the maximum error of different Q values estimation(Q>15)is less than 10%. 展开更多
关键词 Q value estimation time-frequency spectrum ST Window factor Ultrasonic attenuation
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A NEW HYBRID WAVELET-KALMAN FILTER METHOD FOR THE ESTIMATION OF DYNAMIC SYSTEM 被引量:2
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作者 Wen Chenglin Xie Jin +1 位作者 Zhou Funa Wen Chuanbo 《Journal of Electronics(China)》 2006年第1期139-143,共5页
A new hybrid wavelet-Kalman filter method for the estimation of dynamic system is developed, Using this method, the real-time multiscale estimation of the dynamic system is implemented, and the observation equation es... A new hybrid wavelet-Kalman filter method for the estimation of dynamic system is developed, Using this method, the real-time multiscale estimation of the dynamic system is implemented, and the observation equation established is for the object signal itself rather than its wavelet decomposition. The simulation results show that this method can be used to estimate the object's state of the stacked system, which is the foundation of multiscale data fusion; besides the performance of the new algorithm developed in the letter is almost optimal. 展开更多
关键词 REAL-TIME Multiscale estimation dynamic system Wavelet transform Kalman filter
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Target threat estimation based on discrete dynamic Bayesian networks with small samples 被引量:2
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作者 YE Fang MAO Ying +1 位作者 LI Yibing LIU Xinrui 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2022年第5期1135-1142,共8页
The accuracy of target threat estimation has a great impact on command decision-making.The Bayesian network,as an effective way to deal with the problem of uncertainty,can be used to track the change of the target thr... The accuracy of target threat estimation has a great impact on command decision-making.The Bayesian network,as an effective way to deal with the problem of uncertainty,can be used to track the change of the target threat level.Unfortunately,the traditional discrete dynamic Bayesian network(DDBN)has the problems of poor parameter learning and poor reasoning accuracy in a small sample environment with partial prior information missing.Considering the finiteness and discreteness of DDBN parameters,a fuzzy k-nearest neighbor(KNN)algorithm based on correlation of feature quantities(CF-FKNN)is proposed for DDBN parameter learning.Firstly,the correlation between feature quantities is calculated,and then the KNN algorithm with fuzzy weight is introduced to fill the missing data.On this basis,a reasonable DDBN structure is constructed by using expert experience to complete DDBN parameter learning and reasoning.Simulation results show that the CF-FKNN algorithm can accurately fill in the data when the samples are seriously missing,and improve the effect of DDBN parameter learning in the case of serious sample missing.With the proposed method,the final target threat assessment results are reasonable,which meets the needs of engineering applications. 展开更多
关键词 discrete dynamic Bayesian network(DDBN) parameter learning missing data filling Bayesian estimation
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Small Sample Estimation in Dynamic Panel Data Models: A Simulation Study 被引量:1
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作者 Lorelied.A. Santos Erniel B. Barrios 《Open Journal of Statistics》 2011年第2期58-73,共16页
We used simulated data to investigate both the small and large sample properties of the within-groups (WG) estimator and the first difference generalized method of moments (FD-GMM) estimator of a dynamic panel data (D... We used simulated data to investigate both the small and large sample properties of the within-groups (WG) estimator and the first difference generalized method of moments (FD-GMM) estimator of a dynamic panel data (DPD) model. The magnitude of WG and FD-GMM estimates are almost the same for square panels. WG estimator performs best for long panels such as those with time dimension as large as 50. The advantage of FD-GMM estimator however, is observed on panels that are long and wide, say with time dimension at least 25 and cross-section dimension size of at least 30. For small-sized panels, the two methods failed since their optimality was established in the context of asymptotic theory. We developed parametric bootstrap versions of WG and FD-GMM estimators. Simulation study indicates the advantages of the bootstrap methods under small sample cases on the assumption that variances of the individual effects and the disturbances are of similar magnitude. The boostrapped WG and FD-GMM estimators are optimal for small samples. 展开更多
关键词 dynamic Panel Data Model Within-Groups estimATOR First-Difference Generalized Method of MOMENTS estimATOR PARAMETRIC BOOTSTRAP
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Parameter estimation of maneuvering targets in OTHR based on sparse time-frequency representation 被引量:2
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作者 Jinfeng Hu Xuan He +3 位作者 Wange Li Hui Ai Huiyong Li Julan Xie 《Journal of Systems Engineering and Electronics》 SCIE EI CSCD 2016年第3期574-580,共7页
This paper proposes a new method for estimating the parameter of maneuvering targets based on sparse time-frequency transform in over-the-horizon radar(OTHR). In this method, the sparse time-frequency distribution o... This paper proposes a new method for estimating the parameter of maneuvering targets based on sparse time-frequency transform in over-the-horizon radar(OTHR). In this method, the sparse time-frequency distribution of the radar echo is obtained by solving a sparse optimization problem based on the short-time Fourier transform. Then Hough transform is employed to estimate the parameter of the targets. The proposed algorithm has the following advantages: Compared with the Wigner-Hough transform method, the computational complexity of the sparse optimization is low due to the application of fast Fourier transform(FFT). And the computational cost of Hough transform is also greatly reduced because of the sparsity of the time-frequency distribution. Compared with the high order ambiguity function(HAF) method, the proposed method improves in terms of precision and robustness to noise. Simulation results show that compared with the HAF method, the required SNR and relative mean square error are 8 dB lower and 50 dB lower respectively in the proposed method. While processing the field experiment data, the execution time of Hough transform in the proposed method is only 4% of the Wigner-Hough transform method. 展开更多
关键词 over-the-horizon radar(OTHR) maneuvering tar-get parameter estimation sparse time-frequency transform Hough transform
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Analysis of convergence for initial condition estimation of coupled map lattices based on symbolic dynamics
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作者 孙丽莎 康晓云 林兰馨 《Chinese Physics B》 SCIE EI CAS CSCD 2010年第11期179-186,共8页
A novel approach to the inverse problem of diffusively coupled map lattices is systematically investigated by utilizing the symbolic vector dynamics. The relationship between the performance of initial condition estim... A novel approach to the inverse problem of diffusively coupled map lattices is systematically investigated by utilizing the symbolic vector dynamics. The relationship between the performance of initial condition estimation and the structural feature of dynamical system is proved theoretically. It is found that any point in a spatiotemporal coupled system is not necessary to converge to its initial value with respect to sufficient backward iteration, which is directly relevant to the coupling strength and local mapping function. When the convergence is met, the error bound in estimating the initial condition is proposed in a noiseless environment, which is determined by the dimension of attractors and metric entropy of the system. Simulation results further confirm the theoretic analysis, and prove that the presented method provides the important theory and experimental results for better analysing and characterizing the spatiotemporal complex behaviours in an actual system. 展开更多
关键词 coupled mad lattices CONVERGENCE symbolic dynamics initial condition estimation
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Continuous time-varying Q-factor estimation method in the time-frequency domain
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作者 Wang Qing-Han Liu Yang +1 位作者 Liu Cai Zheng Zhi-Sheng 《Applied Geophysics》 SCIE CSCD 2020年第5期844-856,904,共14页
The Q-factor is an important physical parameter for characterizing the absorption and attenuation of seismic waves propagating in underground media,which is of great signifi cance for improving the resolution of seism... The Q-factor is an important physical parameter for characterizing the absorption and attenuation of seismic waves propagating in underground media,which is of great signifi cance for improving the resolution of seismic data,oil and gas detection,and reservoir description.In this paper,the local centroid frequency is defi ned using shaping regularization and used to estimate the Q values of the formation.We propose a continuous time-varying Q-estimation method in the time-frequency domain according to the local centroid frequency,namely,the local centroid frequency shift(LCFS)method.This method can reasonably reduce the calculation error caused by the low accuracy of the time picking of the target formation in the traditional methods.The theoretical and real seismic data processing results show that the time-varying Q values can be accurately estimated using the LCFS method.Compared with the traditional Q-estimation methods,this method does not need to extract the top and bottom interfaces of the target formation;it can also obtain relatively reasonable Q values when there is no eff ective frequency spectrum information.Simultaneously,a reasonable inverse Q fi ltering result can be obtained using the continuous time-varying Q values. 展开更多
关键词 local centroid frequency local time-frequency transform Q-factor estimation shaping regularization
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IDENTIFICATION OF NONLINEAR DYNAMIC SYSTEMS:TIME-FREQUENCY FILTERING AND SKELETON CURVES
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作者 王丽丽 张景绘 《Applied Mathematics and Mechanics(English Edition)》 SCIE EI 2001年第2期210-219,共10页
The nonlinear behavior varying with the instantaneous response was analyzed through the joint time-frequency analysis method for a class of S. D. O. F nonlinear system. A masking operator an definite regions is define... The nonlinear behavior varying with the instantaneous response was analyzed through the joint time-frequency analysis method for a class of S. D. O. F nonlinear system. A masking operator an definite regions is defined and two theorems are presented. Based on these, the nonlinear system is modeled with a special time-varying linear one, called the generalized skeleton linear system (GSLS). The frequency skeleton curve and the damping skeleton curve are defined to describe the main feature of the non-linearity as well. Moreover, an identification method is proposed through the skeleton curves and the time-frequency filtering technique. 展开更多
关键词 system identification nonlinear dynamic system non-stationary signal time-frequency analysis Hilbert transform
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An Approach to Dynamic Asymptotic Estimation for Hurst Index of Network Traffic
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作者 Xiaoyan MA Hongguang LI 《International Journal of Communications, Network and System Sciences》 2010年第2期167-172,共6页
As an important parameter to describe the sudden nature of network traffic, Hurst index typically conducts behaviors of both self-similarity and long-range dependence. With the evolution of network traffic over time, ... As an important parameter to describe the sudden nature of network traffic, Hurst index typically conducts behaviors of both self-similarity and long-range dependence. With the evolution of network traffic over time, more and more data are generated. Hurst index estimation value changes with it, which is strictly consistent with the asymptotic property of long-range dependence. This paper presents an approach towards dynamic asymptotic estimation for Hurst index. Based on the calculations in terms of the incremental part of time series, the algorithm enjoys a considerable reduction in computational complexity. Moreover, the local sudden nature of network traffic can be readily captured by a series of real-time Hurst index estimation values dynamically. The effectiveness and tractability of the proposed approach are demonstrated through the traffic data from OPNET simulations as well as real network, respectively. 展开更多
关键词 Network Traffic Hurst Index dynamic ASYMPTOTIC estimation LONG-RANGE DEPENDENCE
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