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Identification of Errors-in-Variables Systems with General Nonlinear Output Observations and with arma Observation Noises

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Journal of Systems Science & Complexity 2020年第1期33卷 1-14页

作者： SONG Qijiang HUANG Zhiyong School of Mathematics Renmin University of ChinaBeijing 100872China

This paper concerns the identification problem of scalar errors-in-variables(EIV)systems with general nonlinear output observations and arma observation *** independent and identically distributed(i.i.d.)Gaussian inputs with unknown variance,recursive algorithms for estimating the parameters of the EIV systems are *** general nonlinear observations,conditions on the system are imposed to guarantee the almost sure convergence of the estimates.A simulation example is included to justify the theoretical results.

关键词： arma noise α-mixing binary sensor errors-in-variables nonlinear observation recursive estimate stochastic approximation(SA) strongly consistent system identification

Simulation of the growth ring density of Larix olgensis plantation wood with the arma model

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Journal of Forestry Research 2019年第2期30卷 727-737页

作者： Yi Liu Minghui Guo Material Science and Engineering College Northeast Forestry University

Because growth ring data have temporal features, time series analysis can be used to simulate and reveal changes in the life of a tree and contribute to plantation management. In this study, the autoregressive(AR) and moving average modeling method was used to simulate the time series for growth ring density in a larch plantation with different initial planting densities. We adopted the Box–Jenkins method for the modeling, which was initially based on an intuitive analysis of sequence graphs followed by the augmented Dickey–Fuller stationarity test. The order p and q of the arma(p, q) model was determined based on the autocorrelation and partial correlation coefficient figure truncated on the respective *** the residual judgment, the model AR(2) was only fitted to the larch growth ring density series for the plantation with the 1.5 9 2.0 m^2 initial planting *** the residuals series for the other three series was not shown as a white noise sequence, the modeling was rerun. Larch wood from the initial planting density of2.0 9 2.0 m^2 was modeled by arma(2, 1), and arma((1, 5), 3) fitted to the 2.5 9 2.5 m^2 initial planting density,and the 3.0 9 3.0 m^2 was modeled by AR(1, 2, 5).Although the arma modeling can simulate the change in growth ring density, data for the different growth ring time series were described by different models. Thus, time series modeling can be suitable for growth ring data analysis, revealing the time domain and frequency domain of growth ring data.

关键词： Growth ring density Larix olgensis plantation wood arma Modeling Time series analysis

Polar motion prediction using the combination of SSA and arma

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Geodesy and Geodynamics 2023年第4期14卷 368-376页

作者： Qiaoli Kong Jingwei Han Xin Jin Changsong Li Tianfa Wang Qi Bai Yanfei Chen College of Geodesy and Geomatics Shandong University of Science and TechnologyQingdao 266590China State Key Laboratory of Mining Disaster Prevention and Control Co-founded by Shandong Province and Ministry of Science and Technology Shandong University of Science and TechnologyQingdao 266590China

High-precision polar motion(PM) prediction is of important significance in astronomy, geodesy, aviation,hydrographic mapping, interstellar navigation, and so on. SSA can effectively extract the trend and period terms of PM,in the process of achieving high-precision medium-and long-term polar motion prediction,it is necessary to solve the end effect problem and overfitting problem of SSA forecasting method;therefore, arma was applied to decreasethe end effect, and a suitable combination of reconstructed components was determined to avoid the high variance reaction of SSA overfitting. Based on the decomposition and reconstruction of the PM by SSA, the reconstructed components are determined to participate in the SSA iterative fitting model according to the variance contribution rate. The combination of the reconstructed components representing the polar motion period term and the trend term is determined according to the correlation analysis of the selected reconstructed components. After the above work, the principal component prediction sequence is obtained by fitting the period term and the trend term to convergence, respectively, and then, the SSA end effect is modified, and the residual term is predicted based on arma. The test results show that he prediction accuracy of SSA + arma at the front of the X and Y directions are improved by 96.90% and 97.53% compared with those of SSA, respectively,and the forecast accuracy of 365 days are improved by 37.93% and 19.53% in the X and Y directions compared with those of Bulletin A, respectively.

关键词： Polar motion prediction SSA arma End effect

A CONSTRAINED LEAST SQUARES FITTING TECHNIQUE FOR arma MODELING

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Chinese Journal of Acoustics 1989年第2期8卷 157-162页

作者： SUN Yungong(Institute of Acoustics, Academia Sinica) Acad Sinica

Several arma modeling approaches are addressed. In these methods only part of a correlation sequence is employed for estimating parameters. It is satisfying, if the given correlation sequence is of real arma, since an arma process can be completely determined by part of its correlation se -quence. But for the case of a measured correlation sequence the whole sequence may be used to reduce the effect of error on model parameter estimation. In addition, these methods now do not guarantee a nonnegative spectral estimate. In view of the above-mentioned fact, a constrained least squares fitting technique is proposed which utilizes the whole measured correlation sequence and guarantees a nonnegative spectral estimate.

关键词： arma A CONSTRAINED LEAST SQUARES FITTING TECHNIQUE FOR arma MODELING

PARAMETER IDENTIFICATION IN OFFSHORE PLATFORM USING arma MODEL AND TECHNOLOGY OF EXTRACTING FREE VIBRATION SIGNAL

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Applied Mathematics and Mechanics(English Edition) 2003年第4期24卷 449-457页

作者：欧进萍何林肖仪清 HarbinInstituteofTechnology SchoolofCivilEngineering HarbinInstituteofTechnology Harbin150090 P.R.China

A procedure for identifying the dynamic parameter of offshore platform is presented. The present procedure consists of two key features. First uses random decrement (RD) technology to extract free vibration signal in strong noise environment in which it may not white noise. Second technology which called autoregressive moving average (arma) was used to model the data treated by the random decrement method. In order to get rid of the color noise in the output signal response from the offshore platform an imaginary system is added in RD system and make the course of extracting performed under the state of color input by choosing the breakover condition and lead time. For eliminating multi_values of parameters identified, an updating moving average method is used. The dynamic parameters of structure under arbitrary input are identified. Example of the method as applied to a scale_model offshore platform was used to evaluate the technology of efficiency and the value of on_line.

关键词： offshore platform structure arma extracting free vibration signal MA parameter updating parameters identification

ASYMPTOTIC BEHAVIOR OF UNSTABLE arma PROCESSES WITH APPLICATION TO LEAST SQUARES ESTIMATES OF THEIR PARAMETERS

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Acta Mathematicae Applicatae Sinica 1989年第2期5卷 148-168页

作者：安鸿志 Institute of Applied Mathematics Academia Sinica time series x(t) t≥1 is said to be an unstable ARMA process if x(t) satisfies an unstableARMA model such asx(t)=a_1x(t-1)+a_2x(t-2)+…+a_8x(t-s)+w(t)where w(t) is a stationary ARMA process and the characteristic polynomial A(z)=1-a_1z-a_2z~2-…-a_3z~3 has all roots on the unit circle. Asymptotic behavior of sum form 1 to n (x~2(t)) will be studied by showing somerates of divergence of sum form 1 to n (x~2(t)). This kind of properties Will be used for getting the rates of convergenceof least squares estimates of parameters a_1 a_2… a_?

A time series x(t), t≥1, is said to be an unstable arma process if x(t) satisfies an unstablearma model such asx(t)=a_1x(t-1)+a_2x(t-2)+…+a_8x(t-s)+w(t)where w(t) is a stationary arma process; and the characteristic polynomial A(z)=1-a_1z-a_2z^2-…-a_3z^3 has all roots on the unit circle. Asymptotic behavior of sum form 1 to n (x^2(t)) will be studied by showing somerates of divergence of sum form 1 to n (x^2(t)). This kind of properties Will be used for getting the rates of convergenceof least squares estimates of parameters a_1, a_2,…, a_?

关键词： arma ASYMPTOTIC BEHAVIOR OF UNSTABLE arma PROCESSES WITH APPLICATION TO LEAST SQUARES ESTIMATES OF THEIR PARAMETERS

Forecasting Orders with arma in Household Electric Appliance Enterprises Based on Mobile Agent

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Journal of Donghua University(English Edition) 2011年第3期28卷 300-304页

作者：王天日郭顺生 School of Mechanical and Electronic Engineering Wuhan University of Technology

Forecasting orders accurately plays a crucial role for household electric appliance (HEA) enterprises keeping low inventory level. In order to reduce the influence of bullwhip effect, sales data are applied to forecast orders of the next period instead of ordering data. Mobile agent is applied to achieve the sales data from retailers in the data preparation. And the converting approach from sales data of retailers to prediction data is proposed. Autoregressive and moving average (arma) model is introduced to forecast orders and a comparison amongst final prediction error (FPE), Akaike information criterion(AIC), Bayes information criterion(BIC) and Akaike's corrected information criterion(AICC) criterion is shown. The sample test verifies the superiority of AICC; therefore it is applied to identify arma order. Forecasting architecture is established and then the prototype system is tested, at last a case shows the orders prediction of the next quarter and verifies the effectiveness of the proposed method.

关键词： arma orders prediction mobile agent household electric appliance enterprises

On Stability and Trajectory Boundedness in Mean-square Sense for arma Processes

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Acta Mathematicae Applicatae Sinica 2003年第4期19卷 573-580页

作者： Han-Fu ChenAcademy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100080, China Academy of Mathematics and Systems Science Chinese Academy of Sciences 北京 100080

For the multidimensional arma system A(z)y k = C(z)w k it is shown that stability (det A(z) = 0, z : |z| 1) of A(z) is equivalent to the trajectory boundedness in the mean square sense (MSS) which, as a rule, is a consequence of a successful stochastic adaptive control leading the closed-loop of an armaX system to a steady state arma system. In comparison with existing results the stability condition imposed on C(z) is no longer needed. The only structural requirement on the system is that det A(z) and det C(z) have no unstable common factor.

关键词： arma stability boundedness in MSS equivalence

How to compare market efficiency? The Sharpe ratio based on the arma-GARCH forecast

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Financial Innovation 2020年第1期6卷 682-702页

作者： Lin Liu Qiguang Chen Peking University Beijing 100871China

This paper derives a new method for comparing the weak-form efficiency of *** author derives the formula of the Sharpe ratio from the arma-GARCH model and finds that the Sharpe ratio just depends on the coefficients of the AR and MA terms and is not affected by the GARCH *** empirical purposes,the Sharpe ratio can be formulated with a monotonic increasing function of R-squared if the sample size is large *** can utilize the Sharpe ratio to compare weak-form efficiency among different *** results of stochastic simulation demonstrate the validity of the proposed *** author also constructs empirical AR-GARCH models and computes the Sharpe ratio for S&P 500 Index and the SSE Composite Index.

关键词： arma GARCH Measurement of market efficiency Sharpe ratio Stochastic simulation