Cauchy-Schwarz Inequality for Summations

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In summary, the homework equation states that |<u, v>| <= ||u||*||v||. The attempt at a solution is to find two values for u and v that will give the required identity. This is done by solving for u and v using the standard dot product. Once these values are found, the proof is complete.
  • #1
steelphantom
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Homework Statement


Prove that ([tex]\sum_{j=1}^n[/tex]ajbj)2 <= ([tex]\sum_{j=1}^n[/tex]jaj2)([tex]\sum_{j=1}^n[/tex](1/j)bj2)


Homework Equations


Cauchy-Schwarz Inequality: |<u, v>| <= ||u||*||v||


The Attempt at a Solution


If I let u = [tex]\sum_{j=1}^n[/tex]jaj2 and v = [tex]\sum_{j=1}^n[/tex](1/j)bj2, then I have ||u|| = sqrt(<u, u>) and ||v|| = sqrt(<v, v>). Not really sure where to go from here. Any ideas? Thanks!
 
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  • #2
The other form is more helpful in this problem:
<u,v>^2 = <u,u><v,v>

Now, you just have to choose u and v to get the required identity. You know that <u,v> needs to equal to Sum[a_j*b_j]. You also know that the j-th term in the series on the right side is equal to the j-th component of u or v squared.

Can you finish it from here?
 
  • #3
Vid said:
The other form is more helpful in this problem:
<u,v>^2 = <u,u><v,v>

Now, you just have to choose u and v to get the required identity. You know that <u,v> needs to equal to Sum[a_j*b_j]. You also know that the j-th term in the series on the right side is equal to the j-th component of u or v squared.

Can you finish it from here?

First of all, thanks for the help!

Don't you mean <u,v>2 <= <u,u><v,v> ? Also, I'm not sure what you mean by your last sentence. "The series on the right side" is referring to which series? The product of the two series? Anyway, how do I know that? Sorry for these possibly stupid questions, and thanks again for your help.
 
  • #4
Yea, that should be less than or equal to.

I meant that one series was for u and the other for v. With the standard dot product <u,u> = Sum[(u_j)^2].

So Sum[u_j^2] = Sum[j*a_j^2]
and Sum[v_j^2] = Sum[(1/j)*b_j^2]

What does this tell us about what u and v must be equal to?
 
  • #5
Vid said:
Yea, that should be less than or equal to.

I meant that one series was for u and the other for v. With the standard dot product <u,u> = Sum[(u_j)^2].

So Sum[u_j^2] = Sum[j*a_j^2]
and Sum[v_j^2] = Sum[(1/j)*b_j^2]

What does this tell us about what u and v must be equal to?

I don't think I'm seeing it. u_j = sqrt(j)*a_j and u = Sum[u_j] = Sum[sqrt(j)*a_j] ?
v_j = (1/sqrt(j))*b_j and v = Sum[v_j] = Sum[(1/sqrt(j))*b_j] ?

Is this correct? I don't really see how this helps.
 
  • #6
the cs inequality says <p, q> <= |p||q|, here | | denotes the norm

so (<p, q>)^2 <= |p|^2|q|^2


Set p = (a_1/sqrt(1),..., a_n/sqrt(n)), q= (sqrt(1)*b_1, 2*b_2,..., sqrt(n)*b_n)


so your sum on the left = (<p, q>)^2 <= |p|^2|q|^2 = the stuff you have on the right

just verify this
 
  • #7
Ok, just to make sure I got it:

Cauchy Schwarz says |<u, v>| <= ||u||*||v||. This implies <u, v>2 <= <u, u><u, v>. Let <u, u> = [tex]\sum[/tex]uj2 = [tex]\sum[/tex]jaj2 and let <v, v> = [tex]\sum[/tex]vj2 = [tex]\sum[/tex](1/j)bj2.

Then we have u = [tex]\sum[/tex]uj = [tex]\sum[/tex]sqrt(j)*aj and v = [tex]\sum[/tex]vj = [tex]\sum[/tex](1/sqrt(j))*bj.

Then we have <u, v> = [tex]\sum[/tex]ujvj = ... = [tex]\sum[/tex]ajbj. Then square both sides to get <u, v>2 = ([tex]\sum[/tex]ajbj)2.

Then after plugging in, this completes the proof. Thanks again for all your help guys!
 

What is the Cauchy-Schwarz Problem?

The Cauchy-Schwarz Problem is a famous mathematical inequality that states that the dot product of two vectors is always less than or equal to the product of their magnitudes. It is named after mathematicians Augustin-Louis Cauchy and Hermann Amandus Schwarz, who independently discovered the inequality in the 19th century.

What is the significance of the Cauchy-Schwarz Problem?

The Cauchy-Schwarz Problem has many important applications in mathematics and other fields such as physics and engineering. It is often used to prove other mathematical theorems and is a fundamental tool in the study of vector spaces and their properties. It also has practical applications in fields such as statistics, where it is used to define measures of correlation between variables.

How is the Cauchy-Schwarz Problem proved?

The Cauchy-Schwarz Problem can be proved using various methods, including algebraic, geometric, and probabilistic approaches. One of the most common methods is the proof by contradiction, where we assume that the inequality is false and then show that it leads to a contradiction. Another popular proof method is using the Cauchy-Schwarz inequality to prove the problem, as the two are closely related.

What are some real-life examples of the Cauchy-Schwarz Problem?

The Cauchy-Schwarz Problem can be seen in many real-life situations, such as calculating the work done by a force on an object, finding the maximum value of a product of two functions, or determining the maximum possible correlation between two variables. It can also be used in optimization problems, such as finding the shortest distance between two points or the maximum area of a rectangle with a fixed perimeter.

Are there any generalizations of the Cauchy-Schwarz Problem?

Yes, there are several generalizations of the Cauchy-Schwarz Problem, including the Hölder's inequality, Minkowski's inequality, and the generalized Cauchy-Schwarz inequality. These generalizations extend the concept of the Cauchy-Schwarz Problem to more than two vectors or to vector spaces with different properties. They are also useful in solving more complex mathematical problems and have various applications in different fields of study.

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