In our previous work published in this journal, we showed how the Hit-And-Run (HAR) procedure enables efficient sampling of criteria weights from a space formed by restricting a simplex with arbitrary linear inequality constraints. In this short communication, we note that the method for generating a basis of the sampling space can be generalized to also handle arbitrary linear equality constra...

To complete the sparse sampling of linear frequency modulation (LFM) signals and estimate parameters, authors proposed an improved finite rate innovation (FRI) system to achieve goal. First build a mathematical model based on Z-transform, then they input LFM signal into modified FRI process output this model, which enables estimation parameters using only four points. The error final experiment...

Abstract The time domain linear sampling method (TD-LSM) solves inverse scattering problems using data by creating an indicator function for the support of unknown scatterer. It involves only solving a integral equation called near-field different from points that probe where scatterer is located. To date, has been used acoustic wave and tested several types scatterers, i.e. sound hard, impedan...

This paper discusses the reliable guaranteed cost control problem of networked control systems with timevarying sampling period and actuator failures for a given quadratic cost function. For linear time-invariant controlled plant, we assume that the time delay is constant and shorter than the sampling period, the sampling is time-varying within a certain known bound, the system is transformed i...

This paper presents a multiply connected neural network designed to estimate the fractal dimension (Df) using the Box-counting method (BCM). Fractal analysis is a powerful shape recognition tool and has been applied to many pattern recognition problems. Additionally, the Box-Counting Method is one of the most popular methods for estimating Df. However, traditional methods used to estimate Df ar...

in this research genetic and phenotypic parameters were estimated using linear and threshold models, for reproductive traits, data from 6 large industrial dairy herd of east azerbaijan province collected by agriculture jihad organization during 10 years (2001-2010). best linear unbiased predictions of traits breeding values were estimated using restricted maximum likelihood method by wombat sof...

In this paper we discuss the importance sampling Monte Carlo methods for pricing options. The classical importance sampling method is used to eliminate the variance caused by the linear part of the logarithmic function of payoff. The variance caused by the quadratic part is reduced by stratified sampling. We eliminate both kinds of variances just by importance sampling. The corresponding space ...

We propose a method based on minimum-variance polynomial approximation to extract system poles from a data set of samples of the impulse response of a linear system. The method is capable of handling the problem under general conditions of sampling and noise characteristics. The superiority of the proposed method is demonstrated by statistical comparison of its performance with the performances...

A partially linear model is often estimated in a two-stage procedure, which involves estimating the nonlinear component conditional on initially estimated linear coefficients. We propose a sampling procedure that aims to simultaneously estimate the linear coefficients and bandwidths involved in the Nadaraya-Watson estimator of the nonlinear component. The performance of this sampling procedure ...

A chromium electroplating bath with the ability to produce homogenous mist was used to evaluate parameters influencing hexavalent chromium (Cr+6) mist sampling methods. The results of 48 Cr+6mist samples collected using the U.S. National Institute for Occupational Safety and Health method 7600...