Lecture 5 Part 1: Derivative of Matrix Determinant and Inverse

Om kurset

Description: The first ~6 minutes are on the topic Norms and Derivatives: Why a norm of the input and output are needed to define a derivative. Now we can find the “matrix gradient” of the determinant function (leading to the “adjugate” matrix), and the “Jacobian” of a matrix inverse. Instructors: Alan Edelman, Steven G. Johnson