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Math429
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Math429 L6

Lecture 6

Chapter II Finite Dimensional Subspaces

Span and Linear Independence 2A

Recall

Proposition 2.22

In a vector space VV, a spanning list {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\}, and an linearly independent list {w1โƒ—,...,wnโƒ—}\{\vec{w_1},...,\vec{w_n}\}. Then mโ‰คnm\leq n.

Definition 2.26

A list {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\} is called a basis if it is a linearly independent spanning list.

Proposition 2.ex.1

A subspace of a finite dimensional vector space is finite-dimensional.

Proof: Let VV be a finite-dimensional vector space and let WW be a subspace of VV

  • Case 1: W={0โƒ—}W=\{\vec{0}\}

  • Case 2: Span{v1โƒ—,...,vkโˆ’1โƒ—}โŠ‚WSpan\{\vec{v_1},...,\vec{v_{k-1}}\}\subset W where v1โƒ—,...,vkโˆ’1โƒ—\vec{v_1},...,\vec{v_{k-1}} is linearly independent

    If W=Span{v1โƒ—,...,vkโˆ’1โƒ—}W=Span\{\vec{v_1},...,\vec{v_{k-1}}\}, done. If not, then there exists vkโˆ’1โƒ—โˆˆW\vec{v_{k-1}}\in W and vkโƒ—โˆˆSpan{v1โƒ—,...,vkโˆ’1โƒ—}\vec{v_k}\cancel{\in} Span\{\vec{v_1},...,\vec{v_{k-1}}\}. This implies Span{v1โƒ—,...,vkโƒ—}โŠ‚WSpan\{\vec{v_1},...,\vec{v_k}\}\subset W. and {v1โƒ—,...,vkโƒ—}\{\vec{v_1},...,\vec{v_k}\} is linearly independent. Continue until Span{v1โƒ—,...,vnโƒ—}=WโŠ‚VSpan\{\vec{v_1},...,\vec{v_n}\}=W\subset V, VV has a finite spanning set,whose size โ‰ฅn\geq n by Prop 2.22

Theorem 2.28

A list {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\} is a basis for VV if and only if every vector vโƒ—โˆˆV\vec{v}\in V can be uniquely written as

vโƒ—=a1v1โƒ—+a2v2โƒ—+...+anvnโƒ—\vec{v}=a_1\vec{v_1}+a_2\vec{v_2}+...+a_n\vec{v_n}

where a1,...,anโˆˆFa_1,...,a_n\in \mathbb{F}

Proof:

โ‡\Leftarrow

If every vโƒ—=a1v1โƒ—+a2v2โƒ—+...+anvnโƒ—\vec{v}=a_1\vec{v_1}+a_2\vec{v_2}+...+a_n\vec{v_n} with unique choice of a1,...,ana_1,...,a_n, we will show {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\} is a basis

Since every vโƒ—\vec{v} is a linear combination of {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\}, we deduce V=Span{v1โƒ—,...,vnโƒ—}V=Span\{\vec{v_1},...,\vec{v_n}\}

And by assumption, 0โƒ—=a1v1โƒ—+a2v2โƒ—+...+anvnโƒ—\vec{0}=a_1\vec{v_1}+a_2\vec{v_2}+...+a_n\vec{v_n} with unique choice of a1,...,anโˆˆFa_1,...,a_n\in \mathbb{F} (this choice is a1=...=an=0a_1=...=a_n=0) It implies {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\} is linearly independent.

So the list {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\} is a basis.

โ‡’\Rightarrow

If {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\} is a basis, we will show that every vโƒ—\vec{v} can be uniquely written as vโƒ—=a1v1โƒ—+a2v2โƒ—+...+anvnโƒ—\vec{v}=a_1\vec{v_1}+a_2\vec{v_2}+...+a_n\vec{v_n} with unique choice of a1,...,anโˆˆFa_1,...,a_n\in \mathbb{F}

Since {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\} is a basis, it must spans VV with each vector being linearly independent.

Since {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\} spans VV, there must be some a1,...,anโˆˆFa_1,...,a_n\in \mathbb{F} such that vโƒ—=a1v1โƒ—+a2v2โƒ—+...+anvnโƒ—\vec{v}=a_1\vec{v_1}+a_2\vec{v_2}+...+a_n\vec{v_n}

Then 0โƒ—=(a1โˆ’b1)v1โƒ—+...+(anโˆ’bn)vnโƒ—\vec{0}=(a_1-b_1)\vec{v_1}+...+(a_n-b_n)\vec{v_n}

Since {v1โƒ—,...,vnโƒ—}\{\vec{v_1},...,\vec{v_n}\} is linearly independent, this implies aiโˆ’bi=0a_i-b_i=0

Lemma 2.30

Every Spanning set of a vector space can we be reduced into a basis.

ideas of Proof:

If the spanning list is not linearly independent, then use Lemma 2.19 to remove a vector.

Lemma 2.32

Every linearly independent list of vectors in a finite dimensional vector space can be extended with a basis.

ideas of Proof:

If {v1โƒ—,...,vkโˆ’1โƒ—}\{\vec{v_1},...,\vec{v_{k-1}}\}, we can always add another vector vkโƒ—โˆˆSpan{v1โƒ—,...,vkโˆ’1โƒ—}\vec{v_k} \cancel{\in} Span\{\vec{v_1},...,\vec{v_{k-1}}\} to increase the span.

Theorem 2.31

Every finite dimensional vector space has a basis

Proposition (2.33)

Suppose that VV is finite-dimensional and UโŠ‚VU\subset V is a subspace, then โˆƒWโŠ‚V\exists W\subset V such that V=UโŠ•WV= U \oplus W

Proof

Since UU is a subspace of VV, then UU is also finite dimensional. Thus UU has a basis {u1โƒ—,...,ukโƒ—}\{\vec{u_1},...,\vec{u_k}\} This list is linearly independent. So we can extend it into a basis for VV, {u1โƒ—,..,ukโƒ—,w1โƒ—,...,wsโƒ—}\{\vec{u_1},..,\vec{u_k},\vec{w_1},...,\vec{w_s}\}. Now let W=Span{u1โƒ—,..,ukโƒ—,w1โƒ—,...,wsโƒ—}W=Span\{\vec{u_1},..,\vec{u_k},\vec{w_1},...,\vec{w_s}\}

Now we need to prove V=UโŠ•WV=U\oplus W.

Since UโŠ‚VU\subset V and WโŠ‚VW\subset V then V+WโŠ‚VV+W\subset V because U+WU+W is the smallest vector space containing UU and WW.

Since {u1โƒ—,..,ukโƒ—,w1โƒ—,...,wsโƒ—}\{\vec{u_1},..,\vec{u_k},\vec{w_1},...,\vec{w_s}\} is a basis of VV, every vโƒ—โˆˆV,vโƒ—โˆˆSpan{u1โƒ—,..,ukโƒ—,w1โƒ—,...,wsโƒ—}\vec{v}\in V, \vec{v}\in Span\{\vec{u_1},..,\vec{u_k},\vec{w_1},...,\vec{w_s}\}

vโƒ—=a1u1โƒ—+...+akukโƒ—+b1w1โƒ—+...+bswsโƒ—\vec{v}=a_1\vec{u_1}+...+a_k\vec{u_k}+b_1\vec{w_1}+...+b_s\vec{w_s}\\

So vโƒ—โˆˆV+W\vec{v}\in V+W. V=V+WV=V+W

If vโƒ—โˆˆUโ‹‚W\vec{v}\in U\bigcap W, then vโƒ—=a1u1โƒ—+...+akukโƒ—โˆˆV\vec{v}=a_1\vec{u_1}+...+a_k\vec{u_k}\in V, vโƒ—=b1w1โƒ—+...+bswsโƒ—โˆˆW\vec{v}=b_1\vec{w_1}+...+b_s\vec{w_s}\in W, but {u1โƒ—,..,ukโƒ—,w1โƒ—,...,wsโƒ—}\{\vec{u_1},..,\vec{u_k},\vec{w_1},...,\vec{w_s}\} should be an linearly independent spanning set. this implies ai,bj=0a_i,b_j=0 So vโƒ—=0\vec{v}=0