Determining orientation with respect to a known reference plays an important role in almost all modes of navigation. As the sensors required for measuring magnetic field have found their way into portable navigation devices, researchers have started investigating their application to orientation estimation in different environments. Nevertheless, the success of these sensors for orientation est...

Using the technique of smoothed perturbation analysis, we consider steady-state performance measures for continuous-time Markov chains and derive a derivative estimator that can be estimated from a single sample path of the chain under consideration. The estimator is applicable to multi-class queueing networks, for which previous in nitesimal perturbation analysis estimators failed. A simple mu...

Waldén, Karlson, and Sun found an elegant explicit expression of backward error for the linear least squares problem. However, it is difficult to compute this quantity as it involves the minimal singular value of certain matrix. In this paper we present a simple estimation to this bound which can be easily computed especially for large problems. Numerical results demonstrate the validity of the...

This paper presents an algorithm to estimate unknown parameters of parachute models from flight-test data. The algorithm is based on the simultaneous-perturbation-stochastic-approximation method to minimize the prediction error (difference between model output and test data). The algorithm is simple to code and requires only the model output. Analytical gradients are not necessary. The algorith...

Seismic data are commonly modeled by a linearization around a smooth background medium in combination with a high frequency approximation. The perturbation of the medium coefficient is assumed to contain the discontinuities. This leads to two inverse problems, first the linearized inverse problem for the perturbation, and second the estimation of the background, which is a priori unknown (veloc...

The aim of this paper is to derive local influence curvatures under various perturbation schemes for elliptical linear models with longitudinal structure. The elliptical class provides a useful generalization of the normal model since it covers both lightand heavy-tailed distributions for the errors, such as Student-t, power exponential, contaminated normal, among others. It is well known that ...

Speech separation can be treated as a mask estimation problem where interference-dominant portions are masked in a timefrequency representation of noisy speech. In supervised speech separation, a classifier is typically trained on a mixture set of speech and noise. Improving the generalization of a classifier is challenging, especially when interfering noise is strong and nonstationary. Expansi...

in this paper, elzaki homotopy perturbation method is employed for solving linear and nonlinear differential equations with a variable coffecient. this method is a combination of elzaki transform and homotopy perturbation method. the aim of using elzaki transform is to overcome the deficiencies that mainly caused by unsatised conditions in some semi-analytical methods such as homotopy perturbat...

Rolls in finite Prandtl number rotating convection with free-slip top and bottom boundary conditions are shown to be unstable with respect to small angle perturbations for any value of the rotation rate. This instability is driven by the horizontal mean flow whose estimation requires a special singular perturbation analysis. PACS numbers: 47.27.Te, 47.20.Bp, 47.32.-y, 47.20.-Lz

Considering a Multi-Objective Optimization problem for a Dynamic System, we propose a controller that drives this system into a point on the Pareto front.At such a point, no change in any control variable can be made without deteriorating one of the objectives. Gradient Estimators are the core of this controller. A sinusoidal Perturbation based gradient estimation approach is adopted.