8.1 VECTOR SPACES
the trivial case in which all the coefficients are zero) then the vectors arelinearly
independent, and no vector in the set can be expressed as a linear sum of the
others.
If, in a given vector space, there exist sets ofNlinearly independent vectors,
but no set ofN+ 1 linearly independent vectors, then the vector space is said to
beN-dimensional. (In this chapter we will limit our discussion to vector spaces of
finite dimensionality; spaces of infinite dimensionality are discussed in chapter 17.)
8.1.1 Basis vectors
IfVis anN-dimensional vector space thenanyset ofNlinearly independent
vectorse 1 ,e 2 ,...,eNforms abasisforV.Ifxis an arbitrary vector lying inVthen
the set ofN+ 1 vectorsx,e 1 ,e 2 ,...,eN, must belinearly dependentand therefore
such that
αe 1 +βe 2 +···+σeN+χx= 0 , (8.9)
where the coefficientsα,β,...,χare not all equal to 0, and in particularχ=0.
Rearranging (8.9) we may writexas a linear sum of the vectorseias follows:
x=x 1 e 1 +x 2 e 2 +···+xNeN=
∑N
i=1
xiei, (8.10)
for some set of coefficientsxithat are simply related to the original coefficients,
e.g.x 1 =−α/χ,x 2 =−β/χ, etc. Since anyxlying in the span ofVcan be
expressed in terms of thebasisorbase vectorsei, the latter are said to form
acompleteset. The coefficientsxiare thecomponentsofxwith respect to the
ei-basis. These components areunique, since if both
x=
∑N
i=1
xiei and x=
∑N
i=1
yiei,
then
∑N
i=1
(xi−yi)ei= 0 , (8.11)
which, since theeiare linearly independent, has only the solutionxi=yifor all
i=1, 2 ,...,N.
From the above discussion we see thatanyset ofNlinearly independent
vectors can form a basis for anN-dimensional space. If we choose a different set
e′i,i=1,...,Nthen we can writexas
x=x′ 1 e′ 1 +x′ 2 e′ 2 +···+x′Ne′N=
∑N
i=1
x′ie′i. (8.12)