Understanding Holder's Inequality: A Key Step in Proving Minkowski's Inequality

In summary, the conversation discusses the steps for proving Holder's inequality, which involves normalizing vectors and turning a sum into a single term. The strategy is to turn the sum into a constant 1 and then bring back the complexity for arbitrary vectors. This method can also be applied to the integral form of the inequality.
  • #1
pbandjay
118
0
I am actually attempting the proof for Minkowski's inequality, but have not gotten that far yet. I am stuck on a step in Holder's inequality, and I have a feeling it's something very simple that I am just overlooking...

I have easily been able to show [tex]ab \leq \frac{a^p}{p} + \frac{b^q}{q}[/tex]

And if [tex]a,b[/tex] are normalized vectors then:

[tex]\sum_k a_k b_k \leq \frac{1}{p}\sum_k {a_k}^p + \frac{1}{q}\sum_k {b_k}^q[/tex]

And I am aware that through normalizing the vectors, I am supposed to be able to deduce the formula for Holder's inequality:

[tex]\sum_k a_k b_k \leq (\sum_k {a_k}^p)^{\frac{1}{p}}(\sum_k {b_k}^q)^{\frac{1}{q}}[/tex]

But I just cannot figure this step out for some reason! Please give me at least a hint... :confused:

Thank you in advance!
 
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  • #2
This inequality:
[tex]\sum_k a_k b_k \leq \frac{1}{p}\sum_k {a_k}^p + \frac{1}{q}\sum_k {b_k}^q[/tex]

holds for all vectors, not just those that are normalized.

Whenever there are several things being added and you want to turn them into a single term, a good strategy is to do whatever it takes to turn the sum into a constant 1. Then after things simplify, bring back in the complexity that you threw away, but now the sum is gone. This happens all the time, and I think there is a deep meaning why it works so much, but I don't know what it is.

In this case, if you restrict ||a||p = 1, and ||b||q = 1, then the equation becomes

[tex]\sum_k a_k b_k \leq 1[/tex]

for a and b normalized like so. Now bring back the complexity for arbitrary vectors x and y,

[tex]\sum_k \frac{x_k}{||x||_p} \frac{y_k}{||y||_q} \leq 1[/tex]

[tex]\sum_k x_k y_k \leq ||x||_p ||y||_q[/tex]
 
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  • #3
Oh wow, okay. That's pretty nice and slick. Thank you!
 
  • #4
Also note that the same exact strategy will prove the integral form.
 

FAQ: Understanding Holder's Inequality: A Key Step in Proving Minkowski's Inequality

What is Holder's Inequality for Sums?

Holder's Inequality for Sums is a mathematical inequality that relates the sum of the products of two sequences with the sum of the individual sequences raised to a power. It is named after the German mathematician Otto Holder who first proved it in 1889.

How is Holder's Inequality for Sums used in mathematical analysis?

Holder's Inequality for Sums is commonly used to prove other inequalities and to establish convergence of series in mathematical analysis. It is also used in the study of probability and statistics, and has applications in physics and economics.

What is the formula for Holder's Inequality for Sums?

The formula for Holder's Inequality for Sums is as follows:
(a1 + a2 + ... + an) * (b1 + b2 + ... + bn) ≤ (a1p + a2p + ... + anp)1/p * (b1q + b2q + ... + bnq)1/q
Where p and q are positive real numbers such that 1/p + 1/q = 1.

What is the significance of the exponents p and q in Holder's Inequality for Sums?

The exponents p and q in Holder's Inequality for Sums represent the power to which each term in the sum is raised. The values of p and q determine the strength of the inequality, with smaller values resulting in a stronger inequality.

What are some examples of applications of Holder's Inequality for Sums?

Holder's Inequality for Sums has various applications in mathematics and other fields. For example, it can be used to prove the Cauchy-Schwarz Inequality, which is a fundamental inequality in linear algebra. It is also used in the study of integral transforms, such as the Fourier transform, and in the analysis of stochastic processes in probability theory.

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