‎The ‎method ‎of ‎quasilinearization ‎is ‎an ‎effective ‎tool ‎to ‎solve nonlinear ‎equations ‎when ‎some ‎conditions‎ on ‎the ‎nonlinear term ‎of ‎the ‎problem ‎are ‎satisfi‎‎ed. ‎W‎hen ‎the ‎conditions ‎hold, ‎applying ‎this ‎techniqu‎e ‎gives ‎two ‎sequences of ‎coupled ‎linear ‎equations‎ and ‎the ‎solutions ‎of ‎th‎ese ‎linear ‎equations ‎are quadratically ‎convergent ‎to ‎the ‎solution ‎o...

In this paper, to solve a linear one-dimensional Volterra  integral equation of the second kind. For this purpose using the equation form, we have defined a linear transformation and by using it's conjugate and reproducing kernel functions, we obtain a basis for the functions space.Then we obtain the solution of  integral equation in terms of the basis functions. The examples presented in this ...

In this article differential transformation method (DTMs) has been used to solve neutral functional-differential equations with proportional delays. The method can simply be applied to many linear and nonlinear problems and is capable of reducing the size of computational work while still providing the series solution with fast convergence rate. Exact solutions can also be obtained from the kno...

Tensor Product (TP) model transformation method was proposed recently as an automated gateway between a class of non-linear models and linear matrix inequality based control design. The core of the TP model transformation is the higher order singular value decomposition of a large sized tensor, which requires high computational power that is usually out of a regular computer capacity in case of...

In this study, the general partial differential equation of unsteady groundwater flow through non-homogeneous and anisotropic aquifer was solved by the fully implicit finite difference method with control volume approach. The calibration of permeability and storage coefficients as model parameters was performed by a transformation technique and application of Powell's non-linear optimization me...

1 Summary The goal of blind deconvolution and source separation is to unravel the effects of an unknown linear transformation on a unknown signal source. For blind deconvolution, the transformation is a linear finite-impulse response (FIR) filter, and for blind source separation it is a matrix of mixing coefficients. A general architecture for these blind adaptive algorithms consists of an adju...

Hill cipher is developed using simple linear transformation. It is vulnerable to known-plaintext attack and there exist several methods in the direction of linear transformation to overcome the problems. HCM-EE is an improved method using Eigen value but it is linear and too many mathematical operations. In this study an attempt has been made to introduce nonlinearity to the linear transformati...

A method for solving the descriptor discrete-time linear system is focused. For easily, it is converted to a standard discrete-time linear system by the definition of a derivative state feedback. Then partial eigenvalue assignment is used for obtaining state feedback and solving the standard system. In partial eigenvalue assignment, just a part of the open loop spectrum of the standard linear s...

 In this paper an applied problem, where the response of interest is the number of success in a specific experiment, is considered and by various visions is studied. The effects of outlier values of response on results of a regression analysis are so important to be studied. For this reason, using diagnostic methods, outlier response values are recognized. It is shown that use of arc-sine ...

Jahanshahloo et al. (Appl Math Comput 153:215–224, 2004) propose a method for ranking extremely efficient decision making units (DMUs) in data envelopment analysis (DEA) using super-efficiency technique and l1-norm and they show that the presented method is able to eliminate the existing difficulties in some methods. This paper suggests an alternative transformation to convert the nonlinear mod...