Prove 1-norm is => 2-norm for vectors

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The discussion centers on proving that the 1-norm of a vector, denoted as ||x||1, is greater than or equal to the 2-norm, ||x||2. The relevant equations are ||x||1 = ∑i=1n |xi| and ||x||2 = (∑i=1n |xi|2)0.5. The proof involves comparing the squares of both norms, leading to the conclusion that the square of the sum of absolute values is always greater than or equal to the sum of squares, thus establishing ||x||1 ≥ ||x||2.

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Homework Statement


Show that ##||x||_1\geq ||x||_2##


2. Homework Equations

##||x||_1 = \sum_{i=1}^n |x_i|##
##||x||_2 = (\sum_{i=1}^n |x_i|^2)^.5##

The Attempt at a Solution


I am having a hard time with this, because the question just seems so trivial, that I don't even know how to prove it. By looking at the relevant equations we can easily see that the 1-norm is the sum of the absolute value of each element of x-vector. We also see that the 2-norm is the square root of the sum of squares of each absolute value of each element in x. Just by looking at the definition you can easily see that the 1-norm is always greater or equal to the 2-norm.

is there an actual formal way to do this?
It really just seems trivial to me.
 
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charlies1902 said:

Homework Statement


Show that ##||x||_1\geq ||x||_2##


2. Homework Equations

##||x||_1 = \sum_{i=1}^n |x_i|##
##||x||_2 = (\sum_{i=1}^n |x_i|^2)^.5##

The Attempt at a Solution


I am having a hard time with this, because the question just seems so trivial, that I don't even know how to prove it. By looking at the relevant equations we can easily see that the 1-norm is the sum of the absolute value of each element of x-vector. We also see that the 2-norm is the square root of the sum of squares of each absolute value of each element in x. Just by looking at the definition you can easily see that the 1-norm is always greater or equal to the 2-norm.

is there an actual formal way to do this?
It really just seems trivial to me.
Compare ##(||x||_1)^2## and ##(||x||_2)^2##.
 
Ray Vickson said:
Compare ##(||x||_1)^2## and ##(||x||_2)^2##.
Thanks. But isn't that just a different way of saying what I said above?
 
charlies1902 said:
Thanks. But isn't that just a different way of saying what I said above?

No. It constitutes a proof, rather than just a claim.
 
Ray Vickson said:
No. It constitutes a proof, rather than just a claim.
Hmmm. I might be missing something here:
So if I square both sides I obtain:
##||x||_1= (\sum |x_i|)^2##
and
##||x||_2=(\sum |x_i|^2)##

Since, the square of sums of absolute values is always greater or equal to the sum of squares, we have proved that ##||x||_1 \geq ||x||_2##.

Is what I just stated considered a proof or claim?
 
charlies1902 said:
Hmmm. I might be missing something here:
So if I square both sides I obtain:
##||x||_1= (\sum |x_i|)^2##
and
##||x||_2=(\sum |x_i|^2)##

Since, the square of sums of absolute values is always greater or equal to the sum of squares, we have proved that ##||x||_1 \geq ||x||_2##.

Is what I just stated considered a proof or claim?

Now it would be a proof if you explained why "square of sums of absolute values is always greater or equal to the sum of squares".

It has to do, of course, with the presence of (non-negative) cross-product terms of the form ##2 |x_1| \cdot |x_j|## in one expansion but not the other.
 

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