Inner (dot) Product Inequality: Proving Nonnegativity

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In summary, the conversation discusses the inner product of x and y in R^n, which is represented as <x,y> = \sum_{i=1}^n x_i y_i. The conversation also mentions the equation <x,x> = \|x\|^2 and poses a problem involving the inner product for all x and y in R^n. The solution involves using the Cauchy-Schwarz inequality to show that the expression is non-negative.
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babyrudin
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Homework Statement



For [tex]x,y \in R^n[/tex], their inner ("dot") product is given by

[tex]<x,y>=\sum_{i=1}^n x_i y_i.[/tex]

Also, we write

[tex]<x,x>=\|x\|^2.[/tex]

Homework Equations



Fix p>1. Show that for all [tex]x,y \in R^n[/tex] we have

[tex]< \|x\|^{p-2}x -\|y\|^{p-2}y, x-y> \geq 0[/tex]

The Attempt at a Solution



Expanding the left-hand side, we can write

[tex]<\|x\|^{p-2}x,x> -<\|y\|^{p-2}y,x>-<\|x\|^{p-2}x,y>+<\|y\|^{p-2}y,y>[/tex]

which further simplifies to

[tex]\|x\|^p +\|y\|^p -(\|x\|^{p-2} +\|y\|^{p-2})<x,y>.[/tex]

Then I'm stuck. How do I show that the above is nonnegative?
 
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  • #2
how about using cauchy-schwartz inequality?
something like this
<x,y><=sqrt(<x,x><y,y>)=||x||*||y||
then you get that what you wrote is greater than:
||x||^p+||y||^p-(||x||^p-2+||y||^p-2)(||x||*||y||)=
x^(p-1)(x-y)+y^(p-1)(y-x)=(x^p-1-y^p-1)(x-y)
now if ||x||>=||y|| then ||x||^p-1>=||y||^p-1
I leave you to check this proposition.
 
  • #3
I've got it now, many many thanks!
 

1. What is an inner product?

An inner product is a mathematical operation that takes two vectors and produces a scalar value. It is similar to the dot product, but it is defined for complex vectors as well as real vectors.

2. What is the Inner (dot) Product Inequality?

The Inner (dot) Product Inequality states that the inner product of two vectors is always greater than or equal to zero. This means that the angle between the two vectors is either 90 degrees or less than 90 degrees.

3. Why is proving nonnegativity important?

Proving nonnegativity is important because it allows us to determine the relationship between two vectors. If the inner product is always greater than or equal to zero, then the vectors are either orthogonal or in the same direction.

4. How do you prove nonnegativity using the Inner (dot) Product Inequality?

To prove nonnegativity using the Inner (dot) Product Inequality, we take the inner product of two vectors and show that it is always greater than or equal to zero. This can be done by expanding the inner product and using properties of vectors and the inequality.

5. What are some applications of the Inner (dot) Product Inequality?

The Inner (dot) Product Inequality has many applications in various fields of mathematics and science. It is commonly used in linear algebra, geometry, and physics. It can also be applied in signal processing, data analysis, and machine learning.

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