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Proof that All Norms Defined on a Finite Dimensional Vector Space are Equivalent 📂Banach Space

Proof that All Norms Defined on a Finite Dimensional Vector Space are Equivalent

Theorem 1

All norms defined on a finite-dimensional vector space are equivalent.

Explanation

The fact that all norms defined in Euclidean space are equivalent is a corollary of this theorem.

Proof

Strategy: If we can show that there exists c,C>0c , C >0 satisfying cvαvβCvαc \| v \| _{\alpha} \le \| v \| _{\beta} \le C \| v \| _{\alpha}, then the two norms α\left\| \cdot \right\|_{\alpha} and β\left\| \cdot \right\|_{\beta} are equivalent. The existence of the maximum and minimum values of vβvα\displaystyle { { \| v \| _{\beta} } \over {\| v \| _{\alpha} } } is shown at once through the extreme value theorem.


If a norm is defined in the finite-dimensional vector space XX, then there exists a basis {e1,,en}\left\{ e_{1} , \cdots , e_{n} \right\}. Hence, every vector in XX can be represented as (λ1,,λn)=λ1e1++λnen(\lambda_{1} , \cdots , \lambda_{n} ) = \lambda_{1} e_{1} + \cdots + \lambda_{n} e_{n}. Consider the three norms defined in XX, 1\left\| \cdot \right\|_{1}, 2\left\| \cdot \right\|_{2}, and \left\| \cdot \right\|. Especially \left\| \cdot \right\|,

λ1e1++λnen:=k=1nλk \| \lambda_{1} e_{1} + \cdots + \lambda_{n} e_{n} \| : = \sum_{k=1}^{n} | \lambda_{k} |

is defined as the norm by summing up the absolute values of the coefficients of the linear combination. Now, if we show 1\left\| \cdot \right\|_{1} \sim \left\| \cdot \right\| and 2\left\| \cdot \right\| \sim \left\| \cdot \right\|_{2}, then by the transitivity of the equivalence relation, any two norms satisfy 12\left\| \cdot \right\|_{1} \sim \left\| \cdot \right\|_{2}.

  • Part 1.

    Let’s define the function f:(Cn,)Rf : ( \mathbb{C}^{n} , \left\| \cdot \right\| ) \to \mathbb{R} as f(λ1,,λn)=λ1e1++λnen1f( \lambda_{1} , \cdots , \lambda_{n} ) = \| \lambda_{1} e_{1} + \cdots + \lambda_{n} e_{n} \|_{1}. And define sequences {λ1(j)}jN,,{λn(j)}jN\left\{ \lambda_{1}^{(j)} \right\}_{j \in \mathbb{N} } , \cdots , \left\{ \lambda_{n}^{(j)} \right\}_{j \in \mathbb{N} } such that each converges to λ1,,λn\lambda_{1} , \cdots , \lambda_{n}.

    f(λ1(j),,λn(j))f(λ1,,λn)=λ1(j)e1++λn(j)en1λ1e1++λnen1(λ1(j)e1++λn(j)en)(λ1e1++λnen)1k=1n(λk(j)ekλkek)1k=1nλk(j)λkmax1knek1 \begin{align*} & \left| f( \lambda_{1}^{(j)} , \cdots , \lambda_{n}^{(j)} ) - f( \lambda_{1} , \cdots , \lambda_{n} ) \right| \\ =& \left| \| \lambda_{1}^{(j)} e_{1} + \cdots + \lambda_{n}^{(j)} e_{n} \|_{1} - \| \lambda_{1} e_{1} + \cdots + \lambda_{n} e_{n} \|_{1} \right| \\ \le & \left\| \left( \lambda_{1}^{(j)} e_{1} + \cdots + \lambda_{n}^{(j)} e_{n} \right) - \left( \lambda_{1} e_{1} + \cdots + \lambda_{n} e_{n} \right) \right\|_{1} \\ \le & \sum_{k=1}^{n} \left\| \left( \lambda_{k}^{(j)} e_{k} - \lambda_{k} e_{k} \right) \right\|_{1} \\ \le & \sum_{k=1}^{n} \left| \lambda_{k}^{(j)}- \lambda_{k} \right| \max_{1 \le k \le n} \left\| e_{k} \right\|_{1} \end{align*}

    That is, when jj \to \infty, then f(λ1(j),,λn(j))f(λ1,,λn)0\left| f( \lambda_{1}^{(j)} , \cdots , \lambda_{n}^{(j)} ) - f( \lambda_{1} , \cdots , \lambda_{n} ) \right| \to 0 and thus ff is a continuous function.

  • Part 2.

    The set of vectors in XX whose sum of the absolute values of the coefficients is 11

    S:={λ1e1++λnen : k=1nλk=1,λkC} S := \left\{ \lambda_{1} e_{1} + \cdots + \lambda_{n} e_{n} \ : \ \sum_{k=1}^{n} | \lambda_{k}|=1, \lambda_{k} \in \mathbb{C} \right\}

    is compact, and since ff is continuous, by the extreme value theorem,

    f(S)={λ1e1++λnen1 : k=1nλk=1,λkC} f(S) = \left\{ \| \lambda_{1} e_{1} + \cdots + \lambda_{n} e_{n} \|_{1} \ : \ \sum_{k=1}^{n} | \lambda_{k}|=1, \lambda_{k} \in \mathbb{C} \right\}

    has the minimum value mm and the maximum value MM. Therefore,

    mλ1e1++λnen1M m \le \| \lambda_{1} e_{1} + \cdots + \lambda_{n} e_{n} \|_{1} \le M

  • Part 3.

    For (α1e1++αnen)X( \alpha_{1} e_{1} + \cdots + \alpha_{n} e_{n} ) \in X where k=1nαk1\displaystyle \sum_{k=1}^{n} | \alpha_{k}| \ne 1,

    mα1k=1nαke1++αnk=1nαken1M m \le \left\| {{\alpha_{1} } \over { \sum_{k=1}^{n} | \alpha_{k}|}} e_{1} + \cdots + {{\alpha_{n}} \over { \sum_{k=1}^{n} | \alpha_{k}|}} e_{n} \right\|_{1} \le M

    By the properties of norms,

    m1k=1nαkα1e1++αnen1M m \le {{1} \over {\sum_{k=1}^{n} | \alpha_{k}|}} \| \alpha_{1} e_{1} + \cdots + \alpha_{n} e_{n} \|_{1} \le M

    since k=1nαk=α1e1++αnen\displaystyle \sum_{k=1}^{n} | \alpha_{k} | = \| \alpha_{1} e_{1} + \cdots + \alpha_{n} e_{n} \|,

    mα1e1++αnenα1e1++αnen1Mα1e1++αnen m \| \alpha_{1} e_{1} + \cdots + \alpha_{n} e_{n} \| \le \| \alpha_{1} e_{1} + \cdots + \alpha_{n} e_{n} \|_{1} \le M \| \alpha_{1} e_{1} + \cdots + \alpha_{n} e_{n} \|

    Therefore, according to the definition of equivalence of norms,

    1 \left\| \cdot \right\| \sim \left\| \cdot \right\|_{1}

  • Part 4.

    By showing 2\left\| \cdot \right\| \sim \left\| \cdot \right\|_{2} using a similar method, by the transitivity of the equivalence relation,

    12 \left\| \cdot \right\|_{1} \sim \left\| \cdot \right\|_{2}


  1. Kreyszig. (1989). Introductory Functional Analysis with Applications: p75. ↩︎