Inverse Iterative Methods for Solving Nonlinear Equations
Journal Title: Mathematical and Software Engineering - Year 2015, Vol 1, Issue 1
Abstract
In his work we present an approach for obtaining new iterative methods for solving nonlinear equations. This approach can be applicable to arbitrary iterative process which is linearly or quadratically convergent. Analysis of convergence of the new methods demonstrates that the new method preserve the convergence conditions of primitive functions. Numerical examples are given to illustrate the efficiency and performance of presented methods.
Authors and Affiliations
Gyurhan Nedzhibov
Analysis of Environmental and Economic Prospects of Stand-By Solar Powered Systems in Nigeria
Photovoltaic power systems can be used as electrical power source for home to meet its daily energy requirement through direct conversion of solar irradiance into electricity. This paper presents environmental and econom...
Parametric Analysis of Isolated Doubled Edged Hill Diffraction Loss Based on Rounded Edge Diffraction Loss Method and Different Radius of Curvature Methods
In this paper, parametric analysis of isolated doubled edged hill diffraction loss based on rounded edge diffraction loss method is presented. Particularly, the variation of the diffraction loss due to changes in frequen...
Flowchart for Clustered-Based Channel Allocation Management Scheme
In the GSM system, several Base Transceiver Station (BTS) are controlled by a single Base Station Controller (BSC). In this paper, the BTSs in a given BSC is referred to as a cluster. In this paper, flowchart for cluste...
Modified Algorithm for Steganalysis
This paper proposes a modified algorithm for steganalysis based on data compression. The experimental results verify that the proposed steganalysis can detect the altered images with high accuracy.
Predictive Models for Post-Operative Life Expectancy after Thoracic Surgery
This paper studies data mining techniques used in medical diagnosis, particularly for predicting chance of survival of a patient after undergoing thoracic surgery. We discuss models built using decision trees, naive Baye...