Open main menu
Home
Random
Recent changes
Special pages
Community portal
Preferences
About Wikipedia
Disclaimers
Incubator escapee wiki
Search
User menu
Talk
Dark mode
Contributions
Create account
Log in
Editing
Mean value theorem
(section)
Warning:
You are not logged in. Your IP address will be publicly visible if you make any edits. If you
log in
or
create an account
, your edits will be attributed to your username, along with other benefits.
Anti-spam check. Do
not
fill this in!
== Mean value theorem in several variables == The mean value theorem generalizes to real functions of multiple variables. The trick is to use parametrization to create a real function of one variable, and then apply the one-variable theorem. Let <math>G</math> be an open subset of <math>\R^n</math>, and let <math>f:G\to\R</math> be a differentiable function. Fix points <math>x,y\in G</math> such that the line segment between <math>x, y</math> lies in <math>G</math>, and define <math>g(t)=f\big((1-t)x+ty\big)</math>. Since <math>g</math> is a differentiable function in one variable, the mean value theorem gives: :<math>g(1)-g(0)=g'(c)</math> for some <math>c</math> between 0 and 1. But since <math>g(1)=f(y)</math> and <math>g(0)=f(x)</math>, computing <math>g'(c)</math> explicitly we have: :<math>f(y)-f(x)=\nabla f\big((1-c)x+cy\big)\cdot (y-x)</math> where <math>\nabla</math> denotes a [[gradient]] and <math>\cdot</math> a [[dot product]]. This is an exact analog of the theorem in one variable (in the case <math>n=1</math> this ''is'' the theorem in one variable). By the [[Cauchy–Schwarz inequality]], the equation gives the estimate: :<math>\Bigl|f(y)-f(x)\Bigr| \le \Bigl|\nabla f\big((1-c)x+cy\big)\Bigr|\ \Bigl|y - x\Bigr|.</math> In particular, when <math>G</math> is convex and the partial derivatives of <math>f</math> are bounded, <math>f</math> is [[Lipschitz continuity|Lipschitz continuous]] (and therefore [[Uniform continuity|uniformly continuous]]). As an application of the above, we prove that <math>f</math> is constant if the open subset <math>G</math> is connected and every partial derivative of <math>f</math> is 0. Pick some point <math>x_0\in G</math>, and let <math>g(x)=f(x)-f(x_0)</math>. We want to show <math>g(x)=0</math> for every <math>x\in G</math>. For that, let <math>E=\{x\in G:g(x)=0\}</math>. Then <math>E</math> is closed in <math>G</math> and nonempty. It is open too: for every <math>x\in E</math> , :<math>\Big|g(y)\Big|=\Big|g(y)-g(x)\Big|\le (0)\Big|y-x\Big|=0</math> for every <math>y</math> in open ball centered at <math>x</math> and contained in <math>G</math>. Since <math>G</math> is connected, we conclude <math>E=G</math>. The above arguments are made in a coordinate-free manner; hence, they generalize to the case when <math>G</math> is a subset of a Banach space.
Edit summary
(Briefly describe your changes)
By publishing changes, you agree to the
Terms of Use
, and you irrevocably agree to release your contribution under the
CC BY-SA 4.0 License
and the
GFDL
. You agree that a hyperlink or URL is sufficient attribution under the Creative Commons license.
Cancel
Editing help
(opens in new window)