About this document

Bordered Hessian in Constrained Optimization by hishamsauk is a document available to read on EtoBox.

1) Quadratic functions can be expressed in matrix form using a symmetric matrix. The definiteness of a quadratic form depends on the sign of its coefficients. 2) To determine the definiteness of a matrix, its leading principal minors must be evaluated. A matrix is positive/negative definite if its leading principal minors have a consistent sign. 3) When optimizing with constraints, the definiteness of the bordered Hessian matrix determines if the solution is a local minimum or maximum.

Author

hishamsauk

Language

EN