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A ROBUST METHOD FOR FUNDAMENTAL MATRIX ESTIMATION WITH RADIAL DISTORTION
Machine Vision 3D Reconstruction Robust Method Fundamental Matrix Epipolar Geometry SVD
2018/5/16
Fundamental Matrix Estimation is of vital importance in many vision applications and is a core part of 3D reconstruction pipeline. Radial distortion makes the problem to be numerically challenging. We...
Spatial Weights Matrix Selection and Model Averaging for Spatial Autoregressive Models
Model Selection Model Averaging Spatial Econometrics Spatial Autoregressive
2016/1/26
Spatial econometrics relies on spatial weights matrix to specify the cross sectional depen-dence, which might not be unique. This paper proposes a model selection procedure to choose an optimal weight...
Testing the Diagonality of a Large Covariance Matrix in a Regression Setting
Bias-Corrected Test Covariance Diagonality Test High Di- mensional Data
2016/1/26
In multivariate analysis, the covariance matrix associated with a set of vari-ables of interest (namely response variables) commonly contains valuable infor-mation about the dataset. When the dimensio...
Band Width Selection for High Dimensional Covariance Matrix Estimation
Bandable covariance Banding estimator Large p, small n Ratio- consistency Tapering estimator Thresholding estimator
2016/1/25
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance esti-mators. Both estimators require choosing a ban...
Spatial Weights Matrix Selection and Model Averaging for Spatial Autoregressive Models
Model Selection Model Averaging Spatial Econometrics Spatial Autoregressive
2016/1/20
Spatial econometrics relies on spatial weights matrix to specify the cross sectional depen-dence, which might not be unique. This paper proposes a model selection procedure to choose an optimal weight...
Testing the Diagonality of a Large Covariance Matrix in a Regression Setting
Bias-Corrected Test Covariance Diagonality Test High Di- mensional Data Multivariate Analysis
2016/1/20
In multivariate analysis, the covariance matrix associated with a set of vari-ables of interest (namely response variables) commonly contains valuable infor-mation about the dataset. When the dimensio...
Band Width Selection for High Dimensional Covariance Matrix Estimation
Bandable covariance Banding estimator Large p small n
2016/1/20
The banding estimator of Bickel and Levina (2008a) and its tapering version of Cai, Zhang and Zhou (2010), are important high dimensional covariance esti-mators. Both estimators require choosing a ban...
A DEPENDENCY MATRIX TO ASSIST IN THE VISUALIZATION OF GEOSPATIAL IMAGE QUALITY
Visualization Quality Imagery Databases Decision Support
2015/8/31
Professionals of various backgrounds have recognized the value that the use of geospatial imagery can add to their analysis. They
take advantage of the widespread availability of data in vast image ...
Intra and Inter-Rater Reliability of Screening for Movement Impairments: Movement Control Tests from The Foundation Matrix
Movement control movement impairments
2015/8/28
Pre-season screening is well established within the sporting
arena, and aims to enhance performance and reduce injury risk.
With the increasing need to identify potential injury with greater
acc...
On computing the H_infinity-norm of a transfer matrix
Transfer matrix the bisection algorithm computation the transfer matrix the norm
2015/8/13
We present a simple bisection algorithm to compute the H_infinity norm of a transfer matrix. The bisection method is far more efficient than algorithms which involve a search over frequencies, and mor...
A branch and bound methodology for matrix polytope stability problems arising in power systems
Robust matrix of power system the linearized dynamics linear system model robust stability
2015/8/12
This paper proposes a formulation to provide necessary and sufficient conditions for robust stability of a family of matrices modeling linearized power system dynamics. A construction for transforming...
Existence and uniqueness of optimal matrix scalings
diagonal similarity scalings scaled singular value minimization irreducible matrices
2015/8/12
We show that the set of diagonal similarity scalings that minimize the scaled singular value of a matrix is nonempty and bounded if and only if the matrix that is being scaled is irreducible. For an i...
Design and implementation of a parser/solver for SDPs with matrix structure
Control communications information theory statistics computational geometry semidefinite programming problem variable matrix
2015/8/11
A wide variety of analysis and design problems arising in control communication and information theory, statistics, computational geometry and many other fields can be expressed as semidefinite progra...
SDPSOL: a parser/solver for semidefinite programs with matrix structure
Design communication information theory statistics combinatorial optimization computational geometry the circuit design
2015/8/11
A variety of analysis and design problems in control, communication and information theory, statistics, combinatorial optimization, computational geometry, circuit design, and other fields can be expr...
Log-det heuristic for matrix rank minimization with applications to Hankel and Euclidean distance matrices
Positive semi-definite matrix convex sets functions half positive definite matrix distance data
2015/8/11
We present a heuristic for minimizing the rank of a positive semidefinite matrix over a convex set. We use the logarithm of the determinant as a smooth approximation for rank, and locally minimize thi...