Antilinear map

Related lectures (31)

Page 2 of 4

Discusses the misconception that an injective linear map must have M strictly smaller than N.

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

Explores singular value decomposition and its role in understanding linear maps.

Explores the dimension of linear maps and the construction of bases.

Explores linear applications, matrices, injectivity, surjectivity, and compositions of linear maps with examples and demonstrations.

Covers bijective linear maps, invertibility of matrices, isomorphisms, and the rank theorem.

Introduces vector spaces, subspaces, linear maps, and evaluation maps, with examples and exercises for better comprehension.

Covers complex functions, linear and anti-linear functions, harmonic polynomials, rational functions, and exponential functions.

Covers tensor products, symmetric power, and exterior power of vector spaces, including properties and applications.

Introduces the regular representation, a key tool for studying group actions on varieties.