Linear Applications: Definitions and Examples

Related lectures (29)

Page 1 of 3

Covers linear transformations using matrices, focusing on linearity, image, and kernel.

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

Covers the transformation of vectors and tensors in quantum physics.

Explores subspaces in linear algebra and transformations, including kernels and images of linear transformations.

Explores change of basis matrices in linear algebra, emphasizing the importance of understanding matrix transformations between different bases.

Explores Galilean transformations in spacetime, focusing on measurements and coordinate transformations.

Explores the transformation of vectors and tensors in quantum physics, emphasizing Lie groups and algebras.

Explores the properties and applications of the Fourier transform in signal processing and mathematics.

Explores isometries, distinguishing between rotations and reflections, and the preservation of orientation in geometric transformations.

Explores isometries in Euclidean spaces, including translations, rotations, and linear symmetries, with a focus on matrices.