Titlebook: Numerical Methods for Nonlinear Engineering Models; John R. Hauser Book 2009 Springer Science+Business Media B.V. 2009 Simulation.algorith

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ring systems. Hence it is essential than engineers have a toolbox of modeling techniques that can be used to model nonlinear engineering systems. Such a set of basic numerical methods is the topic of this book.978-94-017-7707-0978-1-4020-9920-5

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Curve Fitting and Data Plotting,s” of the fit of the model to the data. Third, one might want to fit a particular physical model with unknown parameters to the data and determine the “best” values of some set of physical parameters when fitted to the data. All of these approaches to data analysis and plotting are considered in thi

intrigue

Statistical Methods and Basic Statistical Functions,he interest in not only in obtaining a smooth curve which gives a good visual representation of the data, but also in determining how accurately various model parameters can be estimated from the experimental data. This is where the statistical properties of the data become important. This emphasis

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Differential Equations: Initial Value Problems,able (or variables) as a function of the independent variable (or variables) at a finite number of values of the dependent variable..This chapter begins by discussing the simple case of a single first-order differential equation. The independent variable will be assumed to be time (t), but the discu

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Differential Equations: Boundary Value Problems,ve approaches must be used in obtaining a solution. One of the features of the numerical solution of such problems, either linear or nonlinear, is that the relative error in the solution tends to increase as such equations are integrated further into the future or further from the initial starting p