I am trying to understand that the Euclidean norm $\|x\|_2 = \left(\sum|x_i|^2\right)^{1/2}$ is in fact a norm and having trouble with the triangle inequality.

All the proofs I have referred to involve the Cauchy-Schwarz inequality. But it seems that this inequality is proved in an inner product space, which has additional properties to a normed space.

So, my question is whether starting with any (possibly infinite dimensional) vector space over $\mathbb{C}$ and taking any algebraic basis for it, can the triangle inequality be proved for the Euclidean norm without making assumptions about an inner product or an orthonormal basis ?

(I don't think that infinite dimensionality should be a problem as any two vectors have finite representations in an algebraic basis).

Can one take the Cauchy-Schwarz inequality "out of context" as an algebraic statement about two finite lists $(x_i)$ and $(y_i)$ and then apply it to the complex coefficients of any algebraic basis to say that $\sum \left|x_iy_i^*\right|\leq (\sum|x_i|^2)^{1/2} (\sum|y_i|^2)^{1/2}$ and then complete the proof of the triangle inequality ?

• The Euclidean norm you have described is the norm associated to the inner product space where the inner product is given by $\left<x,y\right>=\sum x_iy_i$. Commented Oct 14, 2015 at 9:40
• @Donkey_2009. Yes, that's the essence of my question: Can you prove that $(V, \|.\|_2 )$ is a normed space for any algebraic basis without having to establish an orthonormal basis for an inner product ? Commented Oct 14, 2015 at 9:48
• As an answer to your addendum, I don't see why not. Wikipedia has a proof of this inequality. Commented Oct 14, 2015 at 10:39
• @TomCollinge Well, yes, but I don't see why you'd want to. Defining the inner product in this case is easy to do, and the proof using the C-S inequality then has a natural geometric interpretation. Commented Oct 14, 2015 at 11:27
• @Donkey_2009 I was taking the view that a plain vector space, a normed space and an inner product space have increasing structure, and attempting to associate various properties at the lowest necessary level . Having established the Euclidean norm as a valid norm, one can go on to show it is also a foundation for an inner product. Commented Oct 14, 2015 at 11:55

Hint:

Note that the Euclidean norm is a particular case of a $p$-norm and for these norms the triangle inequality can be proved using the Minkowky inequality.

Anyway, the Euclidean norm is the only $p$-norm that satisfies the parallelogram identity ( see: Determining origin of norm), so it is coming from an inner product.

In an $n$ dimensional real space we can prove the C-S inequality with simply algebraic methods (see here). So, yes, in this case we can proof the triangle inequality without explicitly using an inner product space.

• Thanks, but don't you have to prove it's a norm before you can consider the parallelogram identity ? Commented Oct 14, 2015 at 9:44
• Good point!! I've changed my answer. Commented Oct 14, 2015 at 9:55
• Thanks: I changed the question (added to it actually) - any opinion on my addendum ? Commented Oct 14, 2015 at 10:29
• I've added something to my answer. Commented Oct 14, 2015 at 18:55
• I think the proof extends to a Euclidean norm on an algebraic basis of an infinite dimensional space (not that such basis is necessarily easy to find) since CS relates two vectors, which will have finite representations in such a basis. But does the wiki reference cover complex coefficients ? I think that since any two lists of n complex numbers could represent vectors in $C^n$ then CS should apply to them: is this correct in your opinion ? Commented Oct 14, 2015 at 19:19

Community wiki: Just to show the C-S proof. We have $$||x+y||_2^2=\sum|x_i+y_i|^2 = \sum \left|x_i^2+2x_iy_i+y_i^2\right|.$$ Then by the triangle inequality (over $|\cdot|$) $$\sum \left|x_i^2+2x_iy_i+y_i^2\right|\leq \sum|x_i|^2+2\sum|x_i||y_i|+\sum|y_i|^2.$$ But, by the Cauchy-Schwarz inequality, $$\sum|x_i|^2+2\sum|x_i||y_i|+\sum|y_i|^2\leq \sum|x_i|^2+2\left(\sum |x_i|^2\right)^{1/2}\left(\sum|y_i|^2\right)^{1/2}+\sum|y_i|^2.$$ But this is just equal to $$\left(\left(\sum |x_i|^2\right)^{1/2}+\left(\sum |y_i|^2\right)^{1/2}\right)^2=\left(||x||_2+||y||_2\right)^2.$$ Hence, $$||x+y||_2\leq ||x||_2+||y||_2.$$ Note

Concerning the comments on the triangle inequality using $|\cdot |$. There is a trivial proof: $$|a+b|^2=(a+b)^2=a^2+b^2+2ab=|a|^2+|b|^2+2ab\leq(|a|+|b|)^2\implies|a+b|\leq |a|+|b|.$$ Hence, $$|x^2+2xy+y^2|\leq|x|^2+|2xy+y^2|\leq|x|^2+|2xy|+|y|^2=|x|^2+2|x||y|+|y|^2.$$

• But you used triangle inequality here... Commented Oct 14, 2015 at 9:33
• @luka5z They used the triangle inequality for the absolute value, but not the 2-norm. Commented Oct 14, 2015 at 9:40
• Yes, that's correct - I've updated the proof to reflect this. Commented Oct 14, 2015 at 9:41
• Thanks for the response. Actually you use the CS inequality to prove the triangle inequality where you say that $\sum \left|2x_iy\right|\leq 2\sum|x_i||y_i|$ . The CS inequality is proved in an inner product space and question is about the validity of this without assuming an inner product space in the first place. Commented Oct 14, 2015 at 9:42
• How does $\sum \left|2x_iy\right|\leq 2\sum|x_i||y_i|$ use CS? Commented Oct 14, 2015 at 10:00