In this paper a non-iterative technique is developed for the correction of faulty antenna array based on matrix pencil technique(MPT). The failure of a sensor in antenna array can damage the radiation power pattern ...In this paper a non-iterative technique is developed for the correction of faulty antenna array based on matrix pencil technique(MPT). The failure of a sensor in antenna array can damage the radiation power pattern in terms of sidelobes level and nulls. In the developed technique, the radiation pattern of the array is sampled to form discrete power pattern information set. Then this information set can be arranged in the form of Hankel matrix(HM) and execute the singular value decomposition(SVD). By removing nonprincipal values, we obtain an optimum lower rank estimation of HM. This lower rank matrix corresponds to the corrected pattern. Then the proposed technique is employed to recover the weight excitation and position allocations from the estimated matrix. Numerical simulations confirm the efficiency of the proposed technique, which is compared with the available techniques in terms of sidelobes level and nulls.展开更多
The phase error estimated by phase gradient autofocus(PGA) is not based on a finite order polynomial mode, so PGA has a good autofocus property for arbitrary order phase error and is fit for high resolution airborne S...The phase error estimated by phase gradient autofocus(PGA) is not based on a finite order polynomial mode, so PGA has a good autofocus property for arbitrary order phase error and is fit for high resolution airborne SAR. But PGA has two shortcomings: first, it has a worse estimation property for fast changing phase error; second, there exists a section of linear phase in the phase error estimated by this algorithm. This paper introduces the idea of rank one phase estimate (ROPE) autofocus technique, and improves PGA. The improved PGA(IPGA) can successfully overcome both these shortcomings of PGA.展开更多
This paper studies a partially nonstationary vector autoregressive(VAR)model with vector GARCH noises.We study the full rank and the reduced rank quasi-maximum likelihood estimators(QMLE)of parameters in the model.It ...This paper studies a partially nonstationary vector autoregressive(VAR)model with vector GARCH noises.We study the full rank and the reduced rank quasi-maximum likelihood estimators(QMLE)of parameters in the model.It is shown that both QMLE of long-run parameters asymptotically converge to a functional of two correlated vector Brownian motions.Based these,the likelihood ratio(LR)test statistic for cointegration rank is shown to be a functional of the standard Brownian motion and normal vector,asymptotically.As far as we know,our test is new in the literature.The critical values of the LR test are simulated via the Monte Carlo method.The performance of this test in finite samples is examined through Monte Carlo experiments.We apply our approach to an empirical example of three interest rates.展开更多
In this paper, we investigate the variable selection problem of the generalized regression models. To estimate the regression parameter, a procedure combining the rank correlation method and the adaptive lasso techniq...In this paper, we investigate the variable selection problem of the generalized regression models. To estimate the regression parameter, a procedure combining the rank correlation method and the adaptive lasso technique is developed, which is proved to have oracle properties. A modified IMO (iterative marginal optimization) algorithm which directly aims to maximize the penalized rank correlation function is proposed. The effects of the estimating procedure are illustrated by simulation studies.展开更多
Clustered interval-censored failure time data often occur in a wide variety of research and application fields such as cancer and AIDS studies. For such data, the failure times of interest are interval-censored and ma...Clustered interval-censored failure time data often occur in a wide variety of research and application fields such as cancer and AIDS studies. For such data, the failure times of interest are interval-censored and may be correlated for subjects coming from the same cluster. This paper presents a robust semiparametric transformation mixed effect models to analyze such data and use a U-statistic based on rank correlation to estimate the unknown parameters. The large sample properties of the estimator are also established. In addition, the authors illustrate the performance of the proposed estimate with extensive simulations and two real data examples.展开更多
基金sypported by the Research Management Centre(RMC),School of Postgraduate Studies(SPS),Communication Engineering Department,Faculty of Electrical Engineering(FKE),Universiti Teknologi Malaysia(UTM),Johor Bahru(Grant Nos.12H09 and 03E20)
文摘In this paper a non-iterative technique is developed for the correction of faulty antenna array based on matrix pencil technique(MPT). The failure of a sensor in antenna array can damage the radiation power pattern in terms of sidelobes level and nulls. In the developed technique, the radiation pattern of the array is sampled to form discrete power pattern information set. Then this information set can be arranged in the form of Hankel matrix(HM) and execute the singular value decomposition(SVD). By removing nonprincipal values, we obtain an optimum lower rank estimation of HM. This lower rank matrix corresponds to the corrected pattern. Then the proposed technique is employed to recover the weight excitation and position allocations from the estimated matrix. Numerical simulations confirm the efficiency of the proposed technique, which is compared with the available techniques in terms of sidelobes level and nulls.
文摘The phase error estimated by phase gradient autofocus(PGA) is not based on a finite order polynomial mode, so PGA has a good autofocus property for arbitrary order phase error and is fit for high resolution airborne SAR. But PGA has two shortcomings: first, it has a worse estimation property for fast changing phase error; second, there exists a section of linear phase in the phase error estimated by this algorithm. This paper introduces the idea of rank one phase estimate (ROPE) autofocus technique, and improves PGA. The improved PGA(IPGA) can successfully overcome both these shortcomings of PGA.
文摘This paper studies a partially nonstationary vector autoregressive(VAR)model with vector GARCH noises.We study the full rank and the reduced rank quasi-maximum likelihood estimators(QMLE)of parameters in the model.It is shown that both QMLE of long-run parameters asymptotically converge to a functional of two correlated vector Brownian motions.Based these,the likelihood ratio(LR)test statistic for cointegration rank is shown to be a functional of the standard Brownian motion and normal vector,asymptotically.As far as we know,our test is new in the literature.The critical values of the LR test are simulated via the Monte Carlo method.The performance of this test in finite samples is examined through Monte Carlo experiments.We apply our approach to an empirical example of three interest rates.
基金supported by National Natural Science Foundation of China(10901162)supported by the Fundamental Research Funds for the Central Universities and the Research Funds of Renmin University of China(10XNF073)supported by China Postdoctoral Science Foundation(2014M550799)
文摘In this paper, we investigate the variable selection problem of the generalized regression models. To estimate the regression parameter, a procedure combining the rank correlation method and the adaptive lasso technique is developed, which is proved to have oracle properties. A modified IMO (iterative marginal optimization) algorithm which directly aims to maximize the penalized rank correlation function is proposed. The effects of the estimating procedure are illustrated by simulation studies.
基金supported by the National Natural Science Foundation of China under Grant Nos. 11471135and 11861030。
文摘Clustered interval-censored failure time data often occur in a wide variety of research and application fields such as cancer and AIDS studies. For such data, the failure times of interest are interval-censored and may be correlated for subjects coming from the same cluster. This paper presents a robust semiparametric transformation mixed effect models to analyze such data and use a U-statistic based on rank correlation to estimate the unknown parameters. The large sample properties of the estimator are also established. In addition, the authors illustrate the performance of the proposed estimate with extensive simulations and two real data examples.