PEIP (version 1.7)

quadlin: Lagrange multiplier technique

Description

Quadratic Linearization

Usage

quadlin(Q, A, b)

Arguments

Q

positive definite symmetric matrix

A

matrix with linearly independent rows

b

data vector

Value

• list:
• x
  vector of solution values
• lambda
  Lagrange multiplier

Details

Solves the problem: min (1/2) t(x)*Q*x with Ax = b. using the Lagrange multiplier technique, where Q is assumed to be symmetric and positive definite and the rows of A are linearly independent.