Results 1  10
of
28
Multistep scattered data interpolation using compactly supported radial basis functions
 J. Comp. Appl. Math
, 1996
"... Abstract. A hierarchical scheme is presented for smoothly interpolating scattered data with radial basis functions of compact support. A nested sequence of subsets of the data is computed efficiently using successive Delaunay triangulations. The scale of the basis function at each level is determine ..."
Abstract

Cited by 69 (12 self)
 Add to MetaCart
(Show Context)
Abstract. A hierarchical scheme is presented for smoothly interpolating scattered data with radial basis functions of compact support. A nested sequence of subsets of the data is computed efficiently using successive Delaunay triangulations. The scale of the basis function at each level is determined from the current density of the points using information from the triangulation. The method is rotationally invariant and has good reproduction properties. Moreover the solution can be calculated and evaluated in acceptable computing time. During the last two decades radial basis functions have become a well established tool for multivariate interpolation of both scattered and gridded data; see [2,7,8,22,25] for some surveys. The major part
Matrix transformations for computing rightmost eigenvalues of large sparse nonsymmetric eigenvalue problems
 IMA J. Numer. Anal
, 1996
"... This paper gives an overview of matrix transformations for finding rightmost eigenvalues of Ax = kx and Ax = kBx with A and B real nonsymmetric and B possibly singular. The aim is not to present new material, but to introduce the reader to the application of matrix transformations to the solution o ..."
Abstract

Cited by 28 (7 self)
 Add to MetaCart
This paper gives an overview of matrix transformations for finding rightmost eigenvalues of Ax = kx and Ax = kBx with A and B real nonsymmetric and B possibly singular. The aim is not to present new material, but to introduce the reader to the application of matrix transformations to the solution of largescale eigenvalue problems. The paper explains and discusses the use of Chebyshev polynomials and the shiftinvert and Cayley ^ transforms as matrix transformations for problems that arise from the discretization df partial differential equations. A few other techniques are described. The reliability of iterative methods is also dealt with by introducing the concept of domain of confidence or trust region. This overview gives the reader an idea of the benefits and the drawbacks of several transformation techniques. We also briefly discuss the current software
DiscreteTime Modal Control for Seismic Structures with Active Bracing System
"... Citations (this article cites 11 articles hosted on the SAGE Journals Online and HighWire Press platforms): ..."
Abstract

Cited by 2 (1 self)
 Add to MetaCart
Citations (this article cites 11 articles hosted on the SAGE Journals Online and HighWire Press platforms):
European Journal of Control (2005)11:1–10 # 2005 EUCA Subspace Identification of Multivariable Hammerstein and Wiener Models
"... In this paper, subspacebased algorithms for the simultaneous identification of the linear and nonlinear parts of multivariable Hammerstein and Wiener models are presented. The proposed algorithms consist basically of two steps. The first one is a standard (linear) subspace algorithm applied to an e ..."
Abstract
 Add to MetaCart
(Show Context)
In this paper, subspacebased algorithms for the simultaneous identification of the linear and nonlinear parts of multivariable Hammerstein and Wiener models are presented. The proposed algorithms consist basically of two steps. The first one is a standard (linear) subspace algorithm applied to an equivalent linear system whose inputs (respectively outputs) are filtered (by the nonlinear functions describing the static nonlinearities) versions of the original inputs (respectively outputs). The second step consists of a 2norm minimization problem which is solved via Singular Value Decomposition. Under weak assumptions, consistency of the estimates can be guaranteed. The performance of the proposed identification algorithms is illustrated through simulation examples.
Geometric Approach to MeasureBased Metric in Image Segmentation
, 2008
"... Abstract The MumfordShah functional and related algorithms for image segmentation involve a tradeoff between a twodimensional image structure and onedimensional parametric curves (contours) that surround objects or distinct regions in the image. We propose an alternative functional that is indepe ..."
Abstract
 Add to MetaCart
(Show Context)
Abstract The MumfordShah functional and related algorithms for image segmentation involve a tradeoff between a twodimensional image structure and onedimensional parametric curves (contours) that surround objects or distinct regions in the image. We propose an alternative functional that is independent of parameterization; it is a geometric functional given in terms of the surfaces representing the data and image in the feature space. The Ɣconvergence technique is combined with the minimal surfaces theory to yield a global generalization of the MumfordShah segmentation function.
The use of Roentgen stereophotogrammetry to study Micromotion Of Orthopaedic Implants
, 2002
"... Roentgen stereophotogrammetry is the most accurate Roentgen technique for threedimensional assessment of micromotion of orthopaedic implants. The reported accuracy of Roentgen Stereophotogrammetric Analysis (RSA) ranges between 0.05 and 0.5 mm for translations and between 0.15j and 1.15j for rotati ..."
Abstract
 Add to MetaCart
Roentgen stereophotogrammetry is the most accurate Roentgen technique for threedimensional assessment of micromotion of orthopaedic implants. The reported accuracy of Roentgen Stereophotogrammetric Analysis (RSA) ranges between 0.05 and 0.5 mm for translations and between 0.15j and 1.15j for rotations. Because of the high accuracy of RSA, small patient groups are in general sufficient to study the effect on prosthetic fixation due to changes in implant design, addition of coatings, or new bone cements. By assessing micromotion of a prosthesis in a shortterm (i.e. 2 years) clinical RSA study, a prediction can be made on the chance of longterm (i.e. 10 years) loosening of the prosthesis. Therefore, RSA is an important measurement tool to screen new developments in prosthetic design, and to prevent large groups of patients from being exposed to potentially inferior designs. In this article, the basics of the RSA technique are explained, and the importance of clinical RSA studies is illustrated with two examples of clinical RSA studies which RSA delivered very valuable information. Thereafter, two recent developments in RSA that have been implemented at Leiden University Medical Center are presented: digital automated measurements in RSA radiographs and modelbased RSA.
CDMA Systems
"... Abstract: The problem of blind adaptive channel estimation in codedivision multiple access systems is considered. Motivated by the iterative power method, used in Numerical Analysis for estimating singular values and singular vectors, we develop RLS and LMS subspace based adaptive algorithms in ord ..."
Abstract
 Add to MetaCart
(Show Context)
Abstract: The problem of blind adaptive channel estimation in codedivision multiple access systems is considered. Motivated by the iterative power method, used in Numerical Analysis for estimating singular values and singular vectors, we develop RLS and LMS subspace based adaptive algorithms in order to identify the impulse response of the multipath channel. The schemes proposed in this paper use only the spreading code of the user of interest and the received data and are therefore blind. Both versions (RLS and LMS) exhibit rapid convergence combined with low computational complexity. With the help of simulations we demonstrate the improved performance of our methods as compared to the already existing techniques in the literature.
Fast algorithms for positive definite matrices structured
"... by orthogonal polynomials ..."
(Show Context)