22 CHAPTER 1. REVIEW OF SOME LINEAR ALGEBRA

By induction, u j =w j and so this reduces to wk+1/ |wk+1|=wk+1. ■This lemma immediately implies the following lemma.

Lemma 1.5.3 Let V be a subspace of dimension p and let {w1, · · · ,wr} be an or-thonormal set of vectors in V . Then this orthonormal set of vectors may be extended toan orthonormal basis for V, {

w1, · · · ,wr,yr+1, · · · ,yp}

Proof: First extend the given linearly independent set {w1, · · · ,wr} to a basis for Vand then apply the Gram Schmidt theorem to the resulting basis. Since {w1, · · · ,wr} isorthonormal it follows from Lemma 1.5.2 the result is of the desired form, an orthonormalbasis extending {w1, · · · ,wr}. ■

Here is another lemma about preserving distance.

Lemma 1.5.4 Suppose R is an m×n matrix with m≥ n and R preserves distances. ThenR∗R = I. Also, if R takes an orthonormal basis to an orthonormal set, then R must preservedistances.

Proof: Since R preserves distances, |Rx|= |x| for every x. Therefore from the axiomsof the dot product,

|x|2 + |y|2 +(x,y)+(y,x) = |x+y|2 = (R(x+y) ,R(x+y))

= (Rx,Rx)+(Ry,Ry)+(Rx,Ry)+(Ry,Rx)

= |x|2 + |y|2 +(R∗Rx,y)+(y,R∗Rx)

and so for all x,y,(R∗Rx−x,y)+(y,R∗Rx−x) = 0

Hence for all x,y,Re(R∗Rx−x,y) = 0

Now for a x,y given, choose α ∈ C such that

α (R∗Rx−x,y) = |(R∗Rx−x,y)|

Then0 = Re(R∗Rx−x,αy) = Reα (R∗Rx−x,y) = |(R∗Rx−x,y)|

Thus |(R∗Rx−x,y)| = 0 for all x,y because the given x,y were arbitrary. Let y =R∗Rx−x to conclude that for all x,

R∗Rx−x= 0

which says R∗R = I since x is arbitrary.Consider the last claim. Let R : Fn→ Fm such that {u1, · · · ,un} is an orthonormal basis

for Fn and {Ru1, · · · ,Run} is also an orthormal set, then∣∣∣∣∣R(

∑i

xiui

)∣∣∣∣∣2

=

∣∣∣∣∣∑ixiRui

∣∣∣∣∣2

= ∑i|xi|2 =

∣∣∣∣∣∑ixiui

∣∣∣∣∣2

With this preparation, here is the big theorem about the right polar factorization.

22 CHAPTER 1. REVIEW OF SOME LINEAR ALGEBRABy induction, wu; = w; and so this reduces to wy41/|weyi] = Wei.This lemma immediately implies the following lemma.Lemma 1.5.3 Let V be a subspace of dimension p and let {w,,--- ,w,} be an or-thonormal set of vectors in V. Then this orthonormal set of vectors may be extended toan orthonormal basis for V,{wy,-+: Wr Uris Up}Proof: First extend the given linearly independent set {w ,--- ,w,} to a basis for Vand then apply the Gram Schmidt theorem to the resulting basis. Since {w1,---,w,} isorthonormal it follows from Lemma 1.5.2 the result is of the desired form, an orthonormalbasis extending {wy ,---,w,}. IHere is another lemma about preserving distance.Lemma 1.5.4 Suppose R is an m Xx n matrix with m > n and R preserves distances. ThenR*R=1I. Also, if R takes an orthonormal basis to an orthonormal set, then R must preservedistances.Proof: Since R preserves distances, |Ra| = |a| for every 2. Therefore from the axiomsof the dot product,Jal? + |u|? + (ay) + (yx) =|e@t+y) =(R(w+y),R(@+y))(Rx,Rx) + (RyRy) + (Ra, Ry) + (Ry, Rx)|x|” + yl? + (R*Ra,y) + (y,R*R2)and so for all x, y,(RR — ay) + (y,R*Ra— a) =0Hence for all x, y,Re (R* Ra —2x,y) =0Now for a x,y given, choose @ € C such thata(R°Re — x,y) =|(RRe— 2, y)|Then0 =Re(R* Ra — x, ay) = Rea (R*Ra—2,y) = |(R*Rx— 2, y)|Thus |(R*Ra —a,y)| = 0 for all x,y because the given x,y were arbitrary. Let y =R*Rax — x to conclude that for all x,R*Rx—x =0which says R*R =I since & is arbitrary.Consider the last claim. Let R: F” > F” such that {u1,--- ,u,} is an orthonormal basisfor F" and {Ru},--- ,Ru,} is also an orthormal set, then2 2 22R [Es] = Vi xiRuj => y |x;| = Yi xiui |i i iiWith this preparation, here is the big theorem about the right polar factorization.