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
This note explains the following topics, Numerical linear algebra, nonlinear optimization, nonlinear least squares, introduction to floating point numbers and rounding error, examples from signal and image processing, control, machine learning.
The resource described here is an overview of numerical methods important in the study of computational science and engineering. The text starts off with Computing with Matrices and Vectors, foundational elements in many algorithms. The note moves forward and explains Direct Methods for Linear Systems of Equations and Direct Methods for Linear Least Squares Problems, important problemsolving aspects in linear algebra. The Filtering Algorithms for data processing are reviewed, while Data Interpolation and Data Fitting in 1D discuss ways of approximating onedimensional data. Approximation of Functions in 1D and Numerical Quadrature introduce the techniques on function approximation and integration. It also discusses Iterative Methods for NonLinear Systems of Equations and Eigenvaluesa critical topic needed for solving complex systems. It finally includes Numerical Integration and Structure Preserving Integration, fundamental to perform numerical calculations with appropriate accuracy in scientific computing.