The Experts below are selected from a list of 327 Experts worldwide ranked by ideXlab platform
Alexandra Chronopoulou - One of the best experts on this subject based on the ideXlab platform.
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self Similarity Parameter estimation and reproduction property for non gaussian hermite processes
Communications on Stochastic Analysis, 2011Co-Authors: Alexandra Chronopoulou, Ciprian A. Tudor, Frederi ViensAbstract:Let (Z (q;H) t )t2(0;1) be a Hermite processes of order q and with Hurst Parameter H 2 ( 1 ;1). This process is H-self-similar, it has stationary increments and it exhibits long-range dependence. This class contains the fractional Brownian motion (for q = 1) and the Rosenblatt process (for q = 2). We study in this paper the variations of Z (q;H) by using multiple Wiener -It^o stochastic integrals and Malliavin calculus. We prove a reproduction property for this class of processes in the sense that the terms appearing in the chaotic decomposition of the their variations give birth to other Hermite processes of dierent orders and with dierent Hurst Parameters. We apply our results to construct a consistent estimator for the self-Similarity Parameter from discrete observations of a Hermite process.
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Self-Similarity Parameter estimation and reproduction property for non-Gaussian Hermite processes
2010Co-Authors: Alexandra Chronopoulou, Frederi Viens, Ciprian TudorAbstract:We consider the class of all the Hermite processes $(Z_{t}^{(q,H)})_{t\in \lbrack 0,1]}$ of order $q\in \mathbf{N}^{\ast }$ and with Hurst Parameter $% H\in (\frac{1}{2},1)$. The process $Z^{(q,H)}$ is $H$-selfsimilar, it has stationary increments and it exhibits long-range dependence identical to that of fractional Brownian motion (fBm). For $q=1$, $Z^{(1,H)}$ is fBm, which is Gaussian; for $q=2$, $Z^{(2,H)}$ is the Rosenblatt process, which lives in the second Wiener chaos; for any $q>2$, $Z^{(q,H)}$ is a process in the $q$th Wiener chaos. We study the variations of $Z^{(q,H)}$ for any $q$, by using multiple Wiener -It\^{o} stochastic integrals and Malliavin calculus. We prove a reproduction property for this class of processes in the sense that the terms appearing in the chaotic decomposition of their variations give rise to other Hermite processes of different orders and with different Hurst Parameters. We apply our results to construct a strongly consistent estimator for the self-Similarity Parameter $H$ from discrete observations of $Z^{(q,H)}$; the asymptotics of this estimator, after appropriate normalization, are proved to be distributed like a Rosenblatt random variable (value at time $1$ of a Rosenblatt process).with self-Similarity Parameter $1+2(H-1)/q$.
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variations and hurst index estimation for a rosenblatt process using longer filters
Electronic Journal of Statistics, 2009Co-Authors: Alexandra Chronopoulou, Frederi Viens, Ciprian A. TudorAbstract:The Rosenblatt process is a self-similar non-Gaussian process which lives in second Wiener chaos, and occurs as the limit of correlated random sequences in so-called “noncentral limit theorems”. It shares the same covariance as fractional Brownian motion. We study the asymptotic distribution of the quadratic variations of the Rosenblatt process based on long filters, including filters based on high-order finite-dierence and waveletbased schemes. We find exact formulas for the limiting distributions, which we then use to devise strongly consistent estimators of the self-Similarity Parameter H. Unlike the case of fractional Brownian motion, no matter now high the filter orders are, the estimators are never asymptotically normal, converging instead in the mean square to the observed value of the Rosenblatt process at time 1.
Tang Wenyan - One of the best experts on this subject based on the ideXlab platform.
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polarimetric interferometric eigenvalue Similarity Parameter and its application in target detection
IEEE Geoscience and Remote Sensing Letters, 2011Co-Authors: Lamei Zhang, Bin Zou, Tang WenyanAbstract:Polarimetric synthetic aperture radar (SAR) interferometry (PolInSAR) combines SAR polarimetry and SAR interferometry and is much more sensitive to the distribution of orientated scatterers compared with polarimetric or interferometric data alone. The polarimetric Similarity Parameter is an efficient Parameter to analyze target characteristics using the Similarity between a target and the canonical target. In this letter, the polarimetric interferometric eigenvalue Similarity Parameter (PIESP) is proposed based on the Similarity between two polarimetric SAR images obtained by two interferometric antennas. The PIESP is defined by the eigenvalues of two polarimetric coherence matrices in the PolInSAR system, and the eigenvalues of polarimetric coherence matrix are independent on the target orientation angle; therefore, the PIESP is rotation invariant. PolInSAR systems use two antennas to measure the same ground area with slightly different image geometry. Thus, the PIESP can be used to distinguish the target based on coherence and Similarity. Then, the target detection method using the PIESP is implemented with the DLR experimental SAR L-band full polarized image of the Oberpfaffenhofen test site of Germany obtained on September 30, 2000. The results confirmed that the proposed model is accurate and effective for the detection and the analysis of buildings in urban areas.
Ciprian A. Tudor - One of the best experts on this subject based on the ideXlab platform.
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self Similarity Parameter estimation and reproduction property for non gaussian hermite processes
Communications on Stochastic Analysis, 2011Co-Authors: Alexandra Chronopoulou, Ciprian A. Tudor, Frederi ViensAbstract:Let (Z (q;H) t )t2(0;1) be a Hermite processes of order q and with Hurst Parameter H 2 ( 1 ;1). This process is H-self-similar, it has stationary increments and it exhibits long-range dependence. This class contains the fractional Brownian motion (for q = 1) and the Rosenblatt process (for q = 2). We study in this paper the variations of Z (q;H) by using multiple Wiener -It^o stochastic integrals and Malliavin calculus. We prove a reproduction property for this class of processes in the sense that the terms appearing in the chaotic decomposition of the their variations give birth to other Hermite processes of dierent orders and with dierent Hurst Parameters. We apply our results to construct a consistent estimator for the self-Similarity Parameter from discrete observations of a Hermite process.
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variations and hurst index estimation for a rosenblatt process using longer filters
Electronic Journal of Statistics, 2009Co-Authors: Alexandra Chronopoulou, Frederi Viens, Ciprian A. TudorAbstract:The Rosenblatt process is a self-similar non-Gaussian process which lives in second Wiener chaos, and occurs as the limit of correlated random sequences in so-called “noncentral limit theorems”. It shares the same covariance as fractional Brownian motion. We study the asymptotic distribution of the quadratic variations of the Rosenblatt process based on long filters, including filters based on high-order finite-dierence and waveletbased schemes. We find exact formulas for the limiting distributions, which we then use to devise strongly consistent estimators of the self-Similarity Parameter H. Unlike the case of fractional Brownian motion, no matter now high the filter orders are, the estimators are never asymptotically normal, converging instead in the mean square to the observed value of the Rosenblatt process at time 1.
Lamei Zhang - One of the best experts on this subject based on the ideXlab platform.
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stokes matrix polarimetric Similarity Parameter and its application in target detection
Remote Sensing Letters, 2012Co-Authors: Lamei Zhang, Bin Zou, Wenyan TangAbstract:Feature extraction and target detection using a polarimetric synthetic aperture radar image is currently of great interest in synthetic aperture radar applications. The polarimetric Similarity Parameter (PSP) is an effective Parameter to analyse target characteristics, and the Similarity between a target and the canonical target can be used for target discrimination. To describe a complex distributed target, a new method to calculate PSP based on the Stokes matrix is proposed. The characteristic of a target can be described and extracted on the basis of PSP, and then a target detection method using Stokes matrix-based PSP is also implemented. The proposed target detection method is demonstrated with the Danish ElectroMagnetic Institute Synthetic Aperture Radar L-band fully polarized images of the Foulum agricultural test site. The results confirmed that the proposed model is accurate and effective for detection and analysis of buildings in urban areas.
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Similarity enhanced target detection algorithm based on multiple polsar Similarity Parameter
International Geoscience and Remote Sensing Symposium, 2011Co-Authors: Lamei Zhang, Bin Zou, Wenyan TangAbstract:Target analysis and detection using Polarimetric Synthetic Aperture Radar (PolSAR) image is currently of great interest in SAR applications. The scattering mechanism may be very complex because of speckle and the vector superposition of the scattering echo. In the existing polarimetric features, Polarimetric Similarity Parameter (PSP) is an effective Parameter to analyze the scattering characteristics. Based on the Similarity or coherence of the target in the multiple PolSAR images, the Multiple PolSAR Similarity Parameter (MPSP) is proposed and defined using the eigenvalues of two polarimetric coherence matrices. Therefore, the characteristic of a target can be described and extracted using MPSP, and then the Similarity-enhanced target detection method based on MPSP is implemented and demonstrated with DLR E-SAR L-band multiple-temporal PolSAR images of Oberpfaffenhofen test site. The results confirmed that the proposed method is effective for detection and analysis of buildings in urban areas.
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building detection based on polarimetric interferometric eigenvalue Similarity Parameter
IEEE Radar Conference, 2011Co-Authors: Lamei Zhang, Bin Zou, Wenyan TangAbstract:Polarimetric SAR interferometry (PolInSAR) combines SAR polarimetry and SAR interferometry and is much more sensitive to the distribution of orientated scatterers comparing to polarimetric or interferometric data alone. Feature extraction and target detection using Polarimetric SAR interferometry (PolInSAR) images are hot issues of SAR image interpretation and application with much theoretical and applicable significance. Polarimetric Similarity Parameter is an efficient Parameter to analyze target characteristics using the Similarity between a target and the canonical target. In this paper, the Polarimetric Interferometric Eigenvalue Similarity Parameter (PIESP) is proposed based on the Similarity between two polarimetric SAR images obtained by two interferometric antennas to analyze target characteristics. PIESP is defined by the eigenvalues of two polarimetric coherence matrices in PolInSAR system, and PIESP is rotated-invariant. PolInSAR systems use two antennas to measure the same ground area with slightly different image geometry. Thus, PIESP can be used to distinguish target based on coherence and Similarity. Then the target detection method using PIESP is implemented with DLR E-SAR L-band full polarized image of the Oberpfaffenhofen test site of Germany, obtained on September 30th, 2000. The results confirmed that the proposed model is accurate and effective for detection and analysis of buildings in urban areas.
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polarimetric interferometric eigenvalue Similarity Parameter and its application in target detection
IEEE Geoscience and Remote Sensing Letters, 2011Co-Authors: Lamei Zhang, Bin Zou, Tang WenyanAbstract:Polarimetric synthetic aperture radar (SAR) interferometry (PolInSAR) combines SAR polarimetry and SAR interferometry and is much more sensitive to the distribution of orientated scatterers compared with polarimetric or interferometric data alone. The polarimetric Similarity Parameter is an efficient Parameter to analyze target characteristics using the Similarity between a target and the canonical target. In this letter, the polarimetric interferometric eigenvalue Similarity Parameter (PIESP) is proposed based on the Similarity between two polarimetric SAR images obtained by two interferometric antennas. The PIESP is defined by the eigenvalues of two polarimetric coherence matrices in the PolInSAR system, and the eigenvalues of polarimetric coherence matrix are independent on the target orientation angle; therefore, the PIESP is rotation invariant. PolInSAR systems use two antennas to measure the same ground area with slightly different image geometry. Thus, the PIESP can be used to distinguish the target based on coherence and Similarity. Then, the target detection method using the PIESP is implemented with the DLR experimental SAR L-band full polarized image of the Oberpfaffenhofen test site of Germany obtained on September 30, 2000. The results confirmed that the proposed model is accurate and effective for the detection and the analysis of buildings in urban areas.
Abdus M Sattar - One of the best experts on this subject based on the ideXlab platform.
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unsteady hydromagnetic free convection flow with hall current mass transfer and variable suction through a porous medium near an infinite vertical porous plate with constant heat flux
International Journal of Energy Research, 1994Co-Authors: Abdus M SattarAbstract:The effects of Hall current on unsteady free convection flow of an MHD viscous incompressible fluid along an infinite vertical porous plate are investigated in the presence of a uniformly applied magnetic field acting in a plane which makes an angle α with the plane transverse to the plate. A Similarity Parameter, taken to be a function of time, is introduced, and the suction velocity is considered to be inversely proportional to this Parameter. Similarity equations are then derived and solved numerically. The effects of the Hall Parameter, the magnetic Parameter and the permeability are discussed and shown graphically.