Friday, 25 May 2018

real analysis - Monotonicity of $ell_p$ norm



Consider a $n$ dimensional space, it is known (Wikipedia) that for $p>r>0$, we have




$$
\|x\|_p\leq\|x\|_r\leq n^{(1/r-1/p)}\|x\|_p.
$$



I have two questions about the above inequality.



$(\bf 1)$. The first is how to show $\|x\|_p\leq\|x\|_r$ when $p,r\leq1$. When $p>r\geq1$, we can define $$f(s)=\|x\|_s,\,\,s\geq1$$ and find out that $$f'(s)=\|x\|_s\left\{-\frac{1}{s^2}\log(\sum_i|x_i|^s)+\frac{1}{s}\frac{\sum_i|x_i|^s\log(|x_i|)}{\sum_i|x_i|^s}\right\}.$$



Then by the concavity of the $\log$ function, we can see that $$\frac{\sum_i|x_i|^s\log(|x_i|)}{\sum_i|x_i|^s}\leq \log\left(\sum_i\frac{|x_i|^s}{\sum_j|x_j|^s}\cdot|x_i|\right).$$
Let $$y_i=\frac{|x_i|^s}{\sum_j|x_j|^s},$$ it is easy to see $\|y\|_{s^*}\leq1$, where $s^*\geq1$ and $1/s+1/s^*=1$. Then, the Hölder's inequality leads to

$$\frac{\sum_i|x_i|^s\log(|x_i|)}{\sum_i|x_i|^s}\leq \log\left(\sum_i\frac{|x_i|^s}{\sum_j|x_j|^s}\cdot|x_i|\right)= \log\left(\sum_iy_i\cdot|x_i|\right)\leq\log(\|x\|_s\|y\|_{s^*})\leq\log\|x\|_s.$$
Therefore, we can conclude $f'(s)\leq0$ and $\|x\|_p\leq\|x\|_r$ is satisfied. However, when $p,r<1$, we do not have $s^*\geq1$ and $\|y\|_{s^*}\leq1$. The last step does not work any more.



(${\bf 2}$). My second question is how to show $\|x\|_r\leq n^{(1/r-1/p)}\|x\|_p.$ In fact, I was trying to show this by solving the following optimization problem:



$$
\max_{\|x\|_p\leq1} \|x\|_r.
$$
But seems it is difficult to derive a closed form solution. The objective function is non-smooth. Is there any elegant way to solve the above optimization problem?




Can anyone give me a hint? Thanks a lot.


Answer



This answers your first question



As for the second question. Consider Holder inequality
$$
\sum\limits_{i=1}^n |a_ib_i|\leq \left(\sum\limits_{i=1}^n |a_i|^{s/(s-1)}\right)^{1-1/s}\left(\sum\limits_{i=1}^n |b_i|^s\right)^{1/s}
$$
with $a_i=1$, $b_i=|x_i|^r$, $s=p/r$.


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