Finite Element Method: Stiffness Matrix and Basis Functions

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (28)

Page 2 of 3

Linear Independence in Vector Spaces

Explores linear independence in vector spaces and the concept of bases.

Linear Applications: Basis and Independence

Covers linear independence, bases of vectors, and solving systems using matrices.

Linear Algebra: Systems and Subspaces

Covers linear systems, vector subspaces, and the kernel and image of linear applications.

Orthogonal Bases in Vector Spaces

Covers orthogonal bases, Gram-Schmidt method, linear independence, and orthonormal matrices in vector spaces.

The Conjugate Gradients Method (CG)

Covers the Conjugate Gradients method for solving linear systems iteratively with quadratic convergence and emphasizes the importance of linear independence among conjugate directions.

Orthogonality and Projection

Covers orthogonality, scalar products, orthogonal bases, and vector projection in detail.

Linear Systems: Factorization and Cholesky

Explores linear systems, Cholesky factorization, LU factorization, and matrix precision.

Linear Systems Resolution

Covers the resolution of linear systems using the Gauss method to determine unique, infinite, or no solutions.

Linear Applications: Matrices and Transformations

Covers linear applications, matrices, transformations, and the principle of superposition.

Orthogonal Sets and Bases

Introduces orthogonal sets and bases, discussing their properties and linear independence.