The Time-Domain Vector Fitting (TD-VF) algorithm for macromodeling of linear multiport systems is presented. A rational approximation for the system matrix transfer function is easily derived from transient input/output port responses. Several validations illustrate the high accuracy of the method.

This paper is concerned with multidimensional exponential fitting modified Runge-Kutta-Nyström (MEFMRKN) methods for the system of oscillatory second-order differential equations q ′′(t) +Mq(t) = f (q(t)), where M is a d × d symmetric and positive semi-definite matrix and f (q) is the negative gradient of a potential scalar U(q). We formulate MEFMRKN methods and show clearly the relationship be...

This paper addresses the problem of finding whether a given set of three-dimensional (3-D) vectors (the object) can be brought to match a second set of vectors (the template) by means of an affine motion, minimizing a measure of the mismatch error and satisfying an assigned set of geometrical constraints. This problem is encountered in many applications of computer vision, robotics, and manufac...

This paper describes a procedure for frequency dependent modeling of power transformers from measured terminal characteristics. The admittance matrix is measured in the frequency domain using a network analyzer and a dedicated measurement setup. Subsequent approximation of the admittance matrix with rational functions using Vector Fitting gives an EMTP-type compatible model suitable for transie...

Vector Fitting (VF) has been applied to reformulate traditional system identification techniques by introducing a partial-fraction basis to avoid ill-conditioned calculation in broadband system identifications. Because of the reliable and versatility of VF, many extensions and applications have been proposed, for example, the macromodeling of linear structures in signal/power integrity analyses...

Fitting of data points by parametric curves and surfaces is demanded in many scientific fields. In this paper we review and analyze existing least squares orthogonal distance fitting techniques in a general numerical optimization framework. Two new geometric variant methods (GTDM and CDM) are proposed. The geometric meanings of existing and modified optimization methods are also revealed.

A modification of the classical technique of Prony for fitting sums of exponential functions to data is considered. The method maximizes the likelihood for the problem (unlike the usual implementation of Prony’s method, which is not even consistent for transient signals), proves to be remarkably effective in practice, and is supported by an asymptotic stability result. Novel features include a ...

 We consider the problem of model selection in vector autoregressive model with Normal innovation. Tests such as Vuong's and Cox's tests are provided for order and model selection, i.e. for selecting the order and a suitable subset of regressors, in vector autoregressive model. We propose a test as a modified log-likelihood ratio test for selecting subsets of regressors. The Europe oil prices, ...

An effort is made to minimize the arithmetic intricacy of signal by using the VHDL module on FPGA. A curve fitting algorithm is used for finding the fundamental frequency of a given signal. Modification of algorithm is reducing the arithmetic complex-city become extinct the cubic solution. This is mature a fast approach for the signal processing and reduced the resultant error .This is made a c...

Vector Fitting is a popular method of constructing rational approximants designed to fit given frequency response measurements. The original method, which we refer to as VF, is based on a least-squares fit to the measurements by a rational function, using an iterative reallocation of the poles of the approximant. We show that one can improve the performance of VF significantly, by using a parti...