Tensor Products and Symmetric Power

Related lectures (28)

Page 2 of 3

Covers normed spaces, dual spaces, Banach spaces, Hilbert spaces, weak and strong convergence, reflexive spaces, and the Hahn-Banach theorem.

Explains linear independence, basis, and matrix rank with examples and exercises.

Covers diagonalization of matrices, eigenvectors, linear maps, and least squares method.

Explores Lorentz transformations, covariant tensors, rotational invariance, and linear transformations in vector spaces.

Covers the theory and applications of bilinear forms in various mathematical contexts.

Explains kernel, image, and linear maps, illustrating concepts with examples.

Covers the basics of linear mapping and coordinate systems.

Explores matrix operations, rank determination, kernel dimensions, and basis concepts in linear algebra.

Covers linear independence, bases, and coordinate systems with examples and theorems.

Covers matrix kernels, images, linear applications, independence, and bases in vector spaces.