In he unrection UI a unil vector U= y Du} = V ƒ •u= f,uj + fyu2. By t e theorem, D„(Duf)= V(Duƒ)·u= :(Duf)u2. Continue this calculation to %3D || that D(Duf)= fxxu¡ + 2 fxyuju2 + e the square to get Du(Duf) = fxx (u1 * (fxx fyy – f,). - fxx (why we can find an open ball B centered at ) such that f,(x, y) < 0 and D(x, y) > x, y) in B. Conclude that f (xo, yo) is a (, y) in B. Show that D„(Duƒ)(x, y) < 0 fo kimum. es 3 to 6: Looking at the gradient vector fiel (or say there are none) where f has a local min differentiable function f(x, y), identify , local maximum, or saddle point. 11 apter 4. Scalar and Vector Fields 6. 5. 11 У 1. Exercises 7 to 16: Find all critical points (if any) of a given function f(x, y) and determine wike they are local extreme points or saddle points. 7. f(x, y) = x2 + y² + xy²

In he unrection UI a unil vector U= y Du} = V ƒ •u= f,uj + fyu2. By t e theorem, D„(Duf)= V(Duƒ)·u= :(Duf)u2. Continue this calculation to %3D || that D(Duf)= fxxu¡ + 2 fxyuju2 + e the square to get Du(Duf) = fxx (u1 * (fxx fyy – f,). - fxx (why we can find an open ball B centered at ) such that f,(x, y) < 0 and D(x, y) > x, y) in B. Conclude that f (xo, yo) is a (, y) in B. Show that D„(Duƒ)(x, y) < 0 fo kimum. es 3 to 6: Looking at the gradient vector fiel (or say there are none) where f has a local min differentiable function f(x, y), identify , local maximum, or saddle point. 11 apter 4. Scalar and Vector Fields 6. 5. 11 У 1. Exercises 7 to 16: Find all critical points (if any) of a given function f(x, y) and determine wike they are local extreme points or saddle points. 7. f(x, y) = x2 + y² + xy²

Linear Algebra: A Modern Introduction

4th Edition

ISBN:9781285463247

Author:David Poole

Publisher:David Poole

Chapter1: Vectors

Section1.1: The Geometry And Algebra Of Vectors

Problem 4EQ

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