Geometric Transformations in R2 and R3

Related lectures (28)

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Explores matrix representations of linear maps and their invariance, using examples and special cases.

Covers matrices, linear applications, vector spaces, and bijective functions.

Explores projections in R³, matrix properties, and trace concepts with practical examples.

Covers the reduction of a linear application and finding corresponding reduced forms and bases.

Covers the determination of matrices associated with linear transformations and explores the kernel and image concepts.

Covers the concept of basis, linear transformations, matrices, inverses, determinants, and bijective transformations.

Covers the basics of linear algebra, including linear maps, bases, and matrix operations.

Emphasizes the importance of using orthogonal bases in linear algebra for representing linear transformations.

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

Explains the diagonalization of linear transformations using eigenvectors and eigenvalues to form a diagonal matrix.