Linear Applications and Matrix Derivatives

Related lectures (25)

Page 1 of 3

Covers differentiability, composition of functions, partial derivatives, Jacobian matrix, and polar coordinates.

Explains partial derivatives, Hessienne matrix, and their properties.

Covers differential calculus applications and reminders, emphasizing the importance of differentiability in mathematical analysis.

Covers functions with values in R^m, discussing limits, partial derivatives, and differentiability.

Explores differentiability in two variables and the chain rule for compositions.

Explains the Wronskian and its role in determining linear independence of solutions to differential equations.

Explores the definition and derivability of functions in differential calculus, emphasizing differentiability at specific points.

Explains differentiability in LR functions and introduces the Jacobian matrix.

Covers linear approximation, parametric derivatives, and differentiability conditions on intervals.

Explores characteristic polynomials, similarity of matrices, and eigenvalues in linear transformations.