Lectures in Basic Computational Numerical Analysis (PDF 168P)
This lecture series provides comprehensive foundational knowledge in the field of numerical computational analysis. Numerical Linear Algebra covers basic matrix operations and solutions of linear systems. The book further goes into the Solution of Nonlinear Equations that shows methods for solving equations which are not linear in form. Finally, it discusses Approximation Theory, showing how functions and data may be approximated. The lectures also cover Numerical Solution of ODEs and PDEs, giving ways to solve these two basic kinds of equations. This resource is intended for students and professionals looking to gain a solid understanding of basic and applied numerical analysis techniques.
Author(s): J. M. McDonough
168 Pages 
Introduction to Numerical Computation
This is an exhaustive PDF written by Lars Elden, Linde Wittmeyer-Koch, and Hans Bruun Nielsen. In fact, this really is an exemplary introduction to numerical computation. The text begins with the basics like error analysis and computer arithmetic, which gives a very solid ground for the origin and handling of numerical errors. It proceeds further to explain more basic topics related to function evaluation, solutions of nonlinear equations, and interpolation techniques. Next, it describes procedures for improving numerical estimates using differentiation and Richardson extrapolation. This is followed by full details of integration, systems of linear equations, and approximation. Finally, ordinary differential equations complete a thorough course of study that will prepare the reader with both the theory and practice that will serve in carrying out numerical computations.
Author(s): Lars Elden, Linde Wittmeyer-Koch, Hans Bruun Nielsen
383 Pages
Numerical Computation UniOviedo
This PDF is prepared by Gonzalo Galiano Casas and Esperanza Garcia Gonzalo from the Department of Mathematics at Oviedo University. With a view to keeping things compact, this document initiates with finite arithmetic and error analysis, which forms the basis necessary for understanding the issue of numerical precision and limitations. It considers methods for nonlinear equations, interpolation, and approximation. Key sections on numerical differentiation and integration give hands-on tools both for data analysis and the solution of mathematical problems. It also covers systems of linear equations and optimization, rounding it out for students and practitioners who might want to apply the numerical methods through a variety of problems.
Author(s): Gonzalo Galiano Casas, Esperanza Garcia Gonzalo, Dept. of Mathematics, Oviedo University
114 Pages
Prof. L. Vandenberghe's lecture note is on applied numerical computing but brings out the practical application aspect. The text covers most areas of numerical linear algebra, nonlinear optimization nonlinear least squares, introduction to floating-point numbers, and rounding errors that are to be needed for understanding the issues of numerical precision. Examples are drawn from signal and image processing, control systems, and machine learning, among other areas, to indicate how these numerical methods are actually applied. This resource aims to fill the gap between theory and practice by providing a practical method for solving computational problems.
Author(s): Prof. L. Vandenberghe
NA Pages
Numerical Methods for Scientific Computing
It gives an explanation of all the different numerical methods of scientific computing. It starts with the basics, which is Root Finding and Orthogonal Functions, solving equations and analyzing functions. Finite Differences and Divided Differences included for the needs in the process of numerical differentiation and interpolation. Interpolation and Curve Fitting are given to outline estimation and modeling. It also includes Z-Transforms and Summation Formulas for signal processing and numerical summation. Quadrature Formulas and Ordinary Differential Equations are explained for integration and the solution of differential equations. Partial Differential Equations, Integral Equations, and Stability and Error Analysis form the advanced topics for numerical methods coverage. Further, Monte Carlo Techniques, Message Passing Interface, and Simulation Modeling are included to point out methods for probabilistic simulations and parallel computing.
Author(s): John Henry Heinbockel
NA Pages
