This book
covers the following topics: Computers for which LAPACK is Suitable, LAPACK Compared with LINPACK and EISPACK, LAPACK and the BLAS, Availability of LAPACK, Commercial Use of LAPACK, Installation of LAPACK, Documentation for LAPACK, Support for LAPACK
and
Errata in LAPACK.
Author(s): E.
Anderson , Z. Bai , C. Bischof , L. S. Blackford , J. Demmel , J. Dongarra , J.
Du Croz , A. Greenbaum , S. Hammarling , A. McKenney and D. Sorensen
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.
This
note introduces elementary programming concepts including variable types, data
structures, and flow control. After an introduction to linear algebra and
probability, it covers numerical methods relevant to mechanical engineering,
including approximation, integration, solution of linear and nonlinear equations, ordinary
differential equations, and deterministic and probabilistic approaches.
Author(s): Prof.
Anthony T. Patera, Prof. Daniel Frey and Prof. Nicholas Hadjiconstantinou
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.
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.