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泛函中的重要定理之 Hahn-Banach 定理

个人学习笔记整理而来, 内容如有错漏欢迎电邮联系. a collection of personal math notes.

Hahn-Banach Theorem is one of the core theorems of linear functional analysis. The Hahn-Banach Theorem in Vector Space is also called Analytic Form of Hahn-Banach Theorem. Two corollaries are especially important: Hahn-Banach Theorem in Normed Vector Space, and Geometric Form of Hahn-Banach Theorem.

Analytic Form

定理.[Hahn-Banach Theorem in Real Vector Space]

Let be a real vector space, and p is a sublinear functional in X, that is, p:X\rightarrow\mathbb{R} is a function satisfies the following properties:

\begin{eqnarray}p(\alpha x) = \alpha p(x),\quad \forall \alpha>0 \text{ and } x\in X,\\p(x+y) \leqslant p(x)+p(y)\quad \forall x,y\in X.\end{eqnarray}
And let Y be a subspace of X, l:Y\rightarrow\mathbb{R} is a linear functional in Y which satisfies
l(y)\leqslant q(y),\quad \forall y\in Y.
Then there exists a linear functional \widetilde{j}:X\rightarrow\mathbb{R}, such that
\widetilde{l}(y)=l(y),\quad \forall y\in Y.\quad \text{ and } \widetilde{l}(y)\leqslant p(x),\quad \forall x\in X.

[证明.]
Two steps to complete this proof.

Step (i). Add one element to Y and form a larger vector space, and proof for this space.

Assume Y\subsetneqq X, Given x_0\in X-Y (Obviously, x_0\neq 0), define the subspace of X

\text{Dom } f:= {(\alpha x_0 +y)\mid \alpha\in \mathbb{R}, y\in Y},

then Y\subset \text{Dom } f.

Claim 1. Exists linear functional f:\text{Dom } f\rightarrow\mathbb{R}, such that

f(y)=l(y)~ \forall y\in Y\quad \text{and} \quad f(x)\leqslant p(x)~ \forall x\in \text{Dom } f.

The problem can be reduced to find a real number \lambda:=f(x_0), such that

f(\alpha x_0 +y) = f(\alpha x_0) + f(y) = \alpha \lambda +l(y)\leqslant p(\alpha x_0 +y), \quad \forall \alpha \in \mathbb{R}, y\in Y.

This inequality holds for \alpha=0, thus \lambda only need to satisfy:

\begin{eqnarray} \lambda\leqslant\alpha ^{-1}[p(\alpha x_0 +y) - l(y)] = p(x_0 + \alpha^{-1} y) - l(\alpha^{-1} y) ,\quad \forall\alpha>0, y\in Y;\\ \lambda\geqslant\alpha ^{-1}[p(\alpha x_0 +y) - l(y)] = -p(-x_0 + \alpha^{-1} y) + l(-\alpha^{-1} y),\quad \forall\alpha<0, y\in Y; \end{eqnarray}

By linearity of l and sublinearity of p, we have
-p(-x_0 + u) + l(u)\leqslant p(x_0 + v) - l(v),\quad \forall u,v \in Y.

Let
a:=\sup_{u\in Y}{-p(-x_0 + u) + l(u)}\leqslant b:=\inf_{v\in Y}{p(x_0 + v) - l(v)},
and chose \lambda that satisfies a<\lambda<b will done.

Step (ii). functionals that satisfy previous property form a set with appropriate order, Zorn’s Lemma gives the existence of \widetilde{l}.

All the linear functionals f:\text{Dom } f\rightarrow\mathbb{R} defined on subspaces of X which contains Y and satisfy the following properties form a set, we denote it by \mathscr{F}:
f(y)=l(y)~ \forall y\in Y\quad \text{and} \quad f(x)\leqslant p(x)~ \forall x\in \text{Dom } f.

\mathscr{F}\neq \varnothing since l\in\mathscr{F}. And \mathscr{F} is partially ordered with relation \preccurlyeq:
\text{Dom }f_1 \subset \text{Dom }f_2, f_1(x)=f_2(x),\quad \forall x\in \text{Dom }f_1.

Given a totally ordered subset \mathscr{E} of \mathscr{F}, let
\text{Dom } g := \bigcup_{f\in \mathscr{E}}\text{Dom } f,
then it is a subspace of X.

Claim 2. \forall x\in \text{Dom }g,
g(x):=f(x),\quad \forall f\in \mathscr{E} \text{ s.t } x\in \text{Dom }f
clearly define a linear functional g:\text{Dom }g\rightarrow \mathbb{R}, and \forall x\in \text{Dom }g, there is g(x)\leqslant p(x).

Let x\in \text{Dom }g such that x\in \text{Dom }f_1 and x\in \text{Dom }f_2, and f_1, f_2\in \mathscr{E}, without loss of generality, assume f_1 \preccurlyeq f_2. Then g(x) = f_1(x)=f_2(x)\leqslant p(x).

If x_1\in \text{Dom }f_1, x_2\in \text{Dom }f_2, then f_1 \preccurlyeq f_2 implies (x_1+x_2)\in \text{Dom }f_2, thus g(x_1 +x_2) = f_2(x_1 +x_2) = f_2(x_1) +f_2(x_2) = g(x_1) +g(x_2); and \forall \alpha \in \mathbb{R}, g(\alpha x_1) = f_1(\alpha x_1) = \alpha f_1(x) = \alpha g(x_1). [This shows that g(x) is a linear functional indeed!]

By construction of g, it is an upper bound of \mathscr{E}. By Zorn’s Lemma, \mathscr{F} has a maximum element \widetilde{l}, it is defined on a subspace \text{Dom }\widetilde{l}\subset X.

Claim 3. \text{Dom }\widetilde{l} = X, and \widetilde{l}\in \mathscr{F} satisfies every property that we required.

Prove this claim by contradiction. Suppose that \widetilde{l}\subsetneqq X, then repeat step (i), a linear functional \widetilde{f}:\text{Dom }\widetilde{f}\rightarrow\mathbb{R} would exist, and it satisfies all the related properties, and \widetilde{l}\preccurlyeq\widetilde{f}. Hence the claim holds.

Theorem is now proved.

Note. Norm and Semi-norm are examples of sublinear functional, but the concept of sublinear functional is more general, since p(\alpha x) = |\alpha|p(x) is only required for \alpha > 0.

定理. [Hahn-Banach Theorem in Complex Vector Space]

Let X be a complex vector space, and p:X\rightarrow\mathbb{R} is a semi-norm in X. And let Y be a subspace of X, l:Y\rightarrow\mathbb{C} is a linear functional in Y which satisfies

|l(y)|\leqslant q(y),\quad \forall y\in Y.

Then there exists a linear functional \widetilde{j}:X\rightarrow\mathbb{C}, such that

\widetilde{l}(y)=l(y),\quad \forall y\in Y,\quad \text{ and } \left|\widetilde{l}(y)\right|\leqslant p(x),\quad \forall x\in X.

Hahn-Banach Theorem in Normed Vector Space

Denote the dual space of a normed space X by X^*.

定理. [Hahn-Banach Theorem in Normed Vector Space]

Let X be a normed vector space, Y is a subspace of X, and let l:Y\rightarrow \mathbb{K} is a continuous linear functional. Then there exists a continuous linear functional \widetilde{l}:X\rightarrow\mathbb{K} that satisfies

\widetilde{l}(y) = l(y) \quad \forall y\in Y, \text{ and } \|\widetilde{l}\| _{X^*} = \|l\| _{Y^*}.

证明. [Here prove the complex case] Let X be a complex normed vector space.

Some notions need to be clarified first: \|\cdot\| is the norm in X; \|\cdot\| _{X^{*}} is the norm in X^{*}; so is \|\cdot\| _{Y^{*}}; and |\cdot| is the norm of complex numbers.

\forall x\in X, let p(x):=\|l\|_{Y^*}\|x\|. p:X\rightarrow\mathbb{C} is a norm (while l\neq 0), thus a sublinear functional. As l is continuous, then

|l(y)|\leqslant\|l\|_{Y^*}\|x\|\quad \forall y\in Y.

By Theorem\ref{THM:HB-Complex}, there exists a linear functional \widetilde{l}:X\rightarrow\mathbb{C} that satisfies

\widetilde{l}(y)=l(y),\quad \forall y\in Y,\quad \text{ and } \left|\widetilde{l}(x)\right|\leqslant p(x) = \|l\|_{Y^*}\|x\|,\quad \forall x\in X.

Hence \widetilde{l}(x) is continuous and

\|l\| _{Y ^*} = \sup _{y\in Y, y\neq 0}\frac{|l(y)|}{\|y\|}\leqslant \sup _{x\in X, x\neq 0}\frac{|l(x)|}{\|x\|} = \left\| \widetilde{l} \right\| _{X ^*}\leqslant \|l\| _{Y^*}.

The real normed space case can be proved in similar way.

Remark. (1) In the case of Hilbert Space, Hahn-Banach Theorem can be proved in a simpler way without using the Axiom of Choice, Furthermore, it the uniqueness of expension is given.

(2) In general, norm-preserving extension is not necessarily unique. several examples can be found in \cite{ref1}\cite{ref2}. But with certain conditions, the uniqueness can be guaranteed (Corollary\ref{COR:HB-TF}).

Geometric Form

Several preparatory knowledge to be mentioned first.

定义.[Hyperplane]

Let X be a normed vector space. A Hyperplane is a set defined as

H:=x\in X\mid f(x)=\alpha},

in which f is a linear functional that is not always zero, and \alpha\in \mathbb{R}. [f=\alpha] is called the equation of hyperplane H.

命题. Hyperplane [f=\alpha] is closed if and only if f is continuous.

定义. [Separation, Strictly Separation]
Let A,B\subset X. A, B are said to be separated by hyperplane [f=\alpha] if

f(x)\leqslant\alpha,\quad \forall x\in A,\quad \text{and } f(x)\geqslant \alpha,\quad \forall x\in B.

A, B are said to be strictly separated by hyperplane [f=\alpha] if \exists \varepsilon>0, such that
f(x)\leqslant\alpha-\varepsilon,\quad \forall x\in A,\quad \text{and } f(x)\geqslant \alpha+\varepsilon,\quad \forall x\in B.

fig1

fig1

定理. [1st Geometric Form]

Let A\subset X, B\subset X are two nonempty convex set. If A is an open set, then there exists a hyperplane which separates A and B.

定理. [2nd Geometric Form]

Let A\subset X, B\subset X are two nonempty convex set. If A is an closed set and B is a compact set, then there exists a hyperplane which strictly separates A and B.

Note. 更多关于 Hahn-Banach 型定理以及 “凸空间”的内容和结果将在另一份笔记中加以陈述.(这些内容非常重要且有意义.)

作者

Zengfk

发布于

2022-07-15

更新于

2022-09-15

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