Skip to main content
Graph
Search
fr
en
Login
Search
All
Categories
Concepts
Courses
Lectures
MOOCs
People
Practice
Publications
Startups
Units
Show all results for
Home
Lecture
Matrix Inversion: Pivoting and Iterative Methods
Graph Chatbot
Related lectures (30)
Previous
Page 1 of 3
Next
Vectorization in Python: Efficient Computation with Numpy
Covers vectorization in Python using Numpy for efficient scientific computing, emphasizing the benefits of avoiding for loops and demonstrating practical applications.
Linear Systems: Iterative Methods
Covers iterative methods for solving linear systems, including Jacobi and Gauss-Seidel methods.
Iterative Methods for Linear Equations
Covers iterative methods for solving linear equations and analyzing convergence, including error control and positive definite matrices.
Numerical Analysis: Linear Systems
Covers the analysis of linear systems, focusing on methods such as Jacobi and Richardson for solving linear equations.
Jacobi and Gauss-Seidel methods
Explains the Jacobi and Gauss-Seidel methods for solving linear systems iteratively.
Linear Systems: Convergence and Methods
Explores linear systems, convergence, and solving methods with a focus on CPU time and memory requirements.
Matrix Construction and Function Manipulation
Covers tips on matrix construction and function manipulation using MATLAB.
Solving the linear system - Nonlinearity
Explores solving linear systems and addressing nonlinearity in numerical flow simulations using multigrid and linearization methods.
Iterative Methods: Linear Systems
Covers iterative methods for solving linear systems and discusses convergence criteria and spectral radius.
Gauss-Seidel Method
Covers the Gauss-Seidel method for solving linear systems through progressive substitution and iterative processes.