We define the maximum norm of a function on $[-1,1]$ by $\|f \|_{\infty} = \underset{-1 \leq x \leq 1}{\max} |f(x)|$. Find $a,b \in \mathbb{R}$ such that $\|ax^2+x+b \|_{\infty}$ get the minimum value.
The minimax problem
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0So, how far have you gotten on this question, Nhan? Where do you get stuck? – 2017-02-02
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0I'm studying uniform approximation. I can find a best approximation quadratic polynomial of $x$ but i don't know how to find the polynomial of the form $ax^2+b$. – 2017-02-02
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0OK, so, how do you find a best approximation quadratic polynomial? – 2017-02-02
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1Sorry, I should write the polynomial of degree at most 2. I use the theorem: " A best approximation polynomial of an odd function is also odd". Therefore the best approximation polynomial of degree at most 2 of $x$ must be odd then it is $x$. – 2017-02-02
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0" A best approximation polynomial of an odd function is also odd" That's true when you are allowed to use any polynomial you like, but here you are trying to approximate the odd function $-x$ by a function restricted to being of the form $ax^2+b$. So the theorem doesn't apply, and my question remains: how do you find a best approximation quadratic polynomial? – 2017-02-02
2 Answers
Here is a cheap solution based on convexity:
Note that for a fixed $x$, the function $(a,b) \mapsto |a x^2+x+b|$ is convex, hence it follows that $f((a,b)) = \max_{|x| \le 1} |a x^2+x+b|$ is convex.
Note that the domain of the $\max$ is symmetric about zero and compute $f(-(a,b))$.
Use this information to compute the minimum value.
We have $f(-(a,b)) = f((a,b))$ and so convexity gives $f((0,0)) \le {1 \over 2} (f((a,b))+ f(-(a,b))) = f((a,b))$. Hence $(a,b) = (0,0)$ is a minimiser.
Notes:
A little work shows that that iff $|a| \le {1 \over 2}$ and $b=-a$, then $f((a,b)) = f((0,0)) = 1$. In particular, while there is an odd function $x \mapsto 0 x^2 + 0$ that best approximates $x \mapsto x$, there is also an even (but not odd) function $x \mapsto {1 \over 2} x^2 - {1 \over 2}$ that best approximates $x \mapsto x$.
A similar approach can be used to show that there is a polynomial of best approximation of an odd function that has only odd powers of $x$. If $g$ is odd, $p_{e,o}(x) = \sum_k e_k x^{2k} + \sum_k o_k x^{2k+1}$ and $f((e,o)) = \max_{|x|\le 1} | p_{e,o}(x) - g(x)|$, then we can show that $f((-e,o)) = f((e,o))$ and so $f((0,o)) \le f((e,o))$, so we need only consider odd degree polynomials.
A simple way to see that the minimum is at $a=b=0$ is as follows.
First, it is easily checked that for $a=b=0$, $\lVert f\rVert_{\infty}=1$. Now, observe that for arbitrary $a,b\in\mathbb{R}$ we have
$$f(1)=a+b+1\\ f(-1)=a+b-1,$$
so that $|f(1)|>1$ whenever $a+b>0$ and $|f(-1)|>1$ whenever $a+b<0$. Moreover, when $a+b=0$, we have $|f(1)|=|f(-1)|=1$. We see that regardless of the situation, $\lVert f \rVert_{\infty} \geq 1$, so $a=b=0$ is indeed a minimum for $\lVert f \rVert_{\infty}$.
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0Can you tell me why you considered $f(1)$ and $f(-1)$? – 2017-02-03
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0Because these $x$ values lie in the boundary of the interval. – 2017-02-03