南航双语矩阵论matritheory第三章部分题解

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研究生矩阵论课后习题答案全习题三

研究生矩阵论课后习题答案全习题三

习题三1.证明以下问题:(1)假设矩阵序列{}m A 收敛于A ,那么{}Tm A 收敛于T A ,{}m A 收敛于A ;(2)假设方阵级数∑∞=0m m m A c 收敛,那么∑∑∞=∞==⎪⎭⎫ ⎝⎛00)(m mT m Tm m m A c A c .证明:(1)设矩阵,,2,1,)()( ==⨯m a A n n m ij m则,)()(n n m ji Tm a A ⨯=,)()(n n m ij m a A ⨯=,,2,1 =m设,)(n n ij a A ⨯=则n n ji T a A ⨯=)(,,)(n n ij a A ⨯=假设矩阵序列{}m A 收敛于A ,即对任意的n j i ,,2,1, =,有ij m ij m a a =∞→)(lim ,则ji m ji m a a =∞→)(lim ,ij m ij m a a =∞→)(lim ,n j i ,,2,1, =,故{}T m A 收敛于TA ,{}m A 收敛于A .(2)设方阵级数∑∞=0m m mA c的部份和序列为,,,,21m S S S ,其中mm m A c A c c S +++= 10.若∑∞=0m m mA c收敛,设其和为S ,即S A cm m m=∑∞=0,或S S m m =∞→lim ,则T Tm m S S =∞→lim .而级数∑∞=0)(m mTmA c的部份和即为T mS ,故级数∑∞=0)(m m T m A c 收敛,且其和为T S ,即∑∑∞=∞==⎪⎭⎫ ⎝⎛00)(m m T m Tm m m A c A c .2.已知方阵序列{}m A 收敛于A ,且{}1-m A ,1-A 都存在,证明:(1)A A m m =∞→lim ;(2){}11lim --∞→=AA mm .证明:设矩阵,,2,1,)()( ==⨯m a A n n m ij m ,)(n n ij a A ⨯=假设矩阵序列{}m A 收敛于A ,即对任意的n j i ,,2,1, =,有ij m ij m a a =∞→)(lim .(1) 由于对任意的n j j j ,,,21 ,有,lim )(k kkj m kj m a a =∞→ n k ,,2,1 =,故∑-∞→nn n j j j m nj m j m j j j j m a a a 2121)()(2)(1)()1(limτ=∑-nn n j j j nj j j j j j a a a 21212121)()1(τ,而∑-=nn n j j j m nj m j m j j j j m a a a A 2121)()(2)(1)()1(τ,∑-=nn n j j j nj j j j j j a a a A 21212121)()1(τ,故A A m m =∞→lim .(1) 因为n n m ij m m A A A ⨯-=)(1)(1,n n ij A AA ⨯-=)(11. 其中)(m ij A ,ij A 别离为矩阵m A 与A 的代数余子式.与(1)类似可证明对任意的n j i ,,2,1, =,有ij m ij m A A =∞→)(lim ,结合A A m m =∞→lim ,有n n m ij m m A A ⨯∞→)(1lim)(=n n ij A A⨯)(1, 即{}11lim --∞→=A A m m .3.设函数矩阵⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=321sin cos sin )(t t e t t t t t t A t ,其中0≠t ,计算),(),(lim 0t A dt d t A t →),(22t A dtd ,)(t A dt d)(t A dt d . 解:依照函数矩阵的极限与导数的概念与计算方式,有(1)⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡=→→→→→→→→→→001011010lim 0lim 1lim lim lim sin limlim cos lim sin lim )(lim 300200000t t e ttt ttt A t t t t tt t t t t t ;(2)⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡--=⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡'''''''''=22323002sin cos 1sin cos )(01)()()sin ()(cos )(sin )(t t e t tt t t tt t e t t t t t t A dt d t t ; (3)⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡----==t e t t t t t t t A dtd dt d t A dt d t 6002cos 2sin )2(0cos sin ))(()(222; (4)=)(t A dt d '3201sin cos sin t t e tt t t tt)2cos 2(sin )sin cos 2(]1)cos (sin sin 3[32t t t t t t t t t t t t t e t +--+--++=(5))(t A dt d =22302sin cos 1sin cos t t e t t t t t tt -- )sin cos (sin 3cos 32t t t t t e t t -+=.4.设函数矩阵⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=-00302)(222x e e x xe e x A x xx x ,计算⎰10)(dx x A 和⎪⎭⎫ ⎝⎛⎰20)(x dt t A dx d .解:依照函数矩阵积分变限积分函数的导数的概念与计算方式,有(1)⎰10)(dx x A =⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎣⎡⎰⎰⎰⎰⎰⎰-0030210102110210102xdx dx e dxe dx x dxxe dx e xx x x ⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎣⎡---=-0023011311)1(21212e e e ; (2)⎪⎭⎫ ⎝⎛⎰20)(x dt t A dx d =)(22x xA =⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡-00302224222222x e e x e x e x x xx. 5.设,))(,),(),((21T n t y t y t y y =A 为n 阶常数对称矩阵,Ay y y f T=)(,证明:(1)dt dy A y dt df T 2=; (2)dtdy y y dt d T222=. 证明:(1)y A y Ay y Ay y dtdfT T T '+'='=)()(y A y Ay y T T T '+'=))((y A y T '=2dtdyA y T 2=,(2)dtdy y yy dt d y dt d T T 2)(22==. 6.证明关于迹的以下公式:(1)X X X tr dX d XX tr dX d T T 2)()(==; (2)T T T B B X tr dXd BX tr dX d ==)()(;(3)X A A AX X tr dXdT T )()(+=. 其中m m ij m n ij n m ij a A b B x X ⨯⨯⨯===)(,)()(.证明:(1)因为∑∑====mi nj ij TTx X X tr XX tr 112)()(,而ij m i n j ij ij x x x 2)(112=∂∂∑∑==, 故X X X tr dXd XX tr dX d T T 2)()(== (2)因为n n mk kj ik x b BX ⨯=∑=)(1,则∑∑====n j mk kj jk TTx b B X tr BX tr 11)()(,而ji n j mk kj jk ij b x b x =∂∂∑∑==)(11, 故T T T B B X tr dXd BX tr dX d ==)()(. (1) 因为,212221212111⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡=mn n n m m T x x x x x x x x x X⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=∑∑∑∑∑∑∑∑∑=========mk kn mk m k k mk mk k mk mk kn k mk k kmk k k mk kn k mk k k mk k k x a xax a x a x axa x a x a x a AX 112111212211211121111故)()()()(11ln 111111∑∑∑∑∑∑======++++=m l mk kn lk ml m k kj lk lj m l m k k lk l Tx a x x a x x a x AX X tr 则))(()(11∑∑==∂∂=∂∂m l mk kj lk lj ij Tij x a x x AX X tr x )]([111∑∑∑===∂∂+∂∂=mk kj lk ij lj mk kj lk ij ljml x a x x x a x x ∑∑==+=ml lj li mk kj ik x a x a 11故X A A X A AX AX X tr dXdT T T )()(+=+=. 7.证明:TT T T T T dX db a dX da b b a dX d +=)(, 其中)(),(X b X a 为向量函数.证明:设T m T m X b X b X b X b X a X a X a X a ))(,),(),(()(,))(,),(),(()(2121 ==,则∑==mi i i TX b X a X b X a 1)()()()(,故它是X 的数量函数,设)()()(X b X a X f T =,有),,,())()((21nTTx f x f x f X b X a dX d ∂∂∂∂∂∂= ⎪⎪⎭⎫ ⎝⎛⎪⎪⎭⎫ ⎝⎛∂∂+∂∂⎪⎪⎭⎫ ⎝⎛∂∂+∂∂=∑∑==m i n i i i n i m i i i i i x X b X a X b x X a x X b X a X b x X a 1111)()()()(,,)()()()( ∑∑∑===∂∂∂∂∂∂=mi i n i m i i i mi i i X b x X a X b x X a X b x X a 11211))()(,,)()(,)()(( ))()(,,)()(,)()((11211∑∑∑===∂∂∂∂∂∂+mi ni i m i i i mi i i x X b X a x X b X a x X b X aTT T TdX db adX da b +=. 8.在2R 中将向量Tx x ),(21表示成平面直角坐标系21,x x 中的点Tx x ),(21,别离画出以下不等式决定的向量Tx x x ),(21=全部所对应的几何图形:(1) ,11≤x (2) ,12≤x (3) 1≤∞x . 解:依照,1211≤+=x x x ,122212≤+=x x x{}1,max 21≤=∞x x x ,作图如下:9.证明对任何nC y x ∈,,总有)(212222y x y x x y y x T T --+=+. 证明:因为y y x y y x x x y x y x yx T T T T T +++=++=+)()(22y y x y y x x x y x y x y x T T T T T +--=--=-)()(22故x y y x y x y x T T +=--+)(212222 10.证明:对任意的nC x ∈,有12x x x≤≤∞.证明:设Tn x x x x ),,,(21 =,那么{}nn n x x x x x x x xx x x x +++=+++==∞21122221221,,,,,max由于{}22122221221)(),,,(max n nn x x x x x x x x x +++≤+++≤ ,故21222x xx≤≤∞,即12x x x≤≤∞.11.设n a a a , ,,21是正实数,证明:对任意nT n C x x x X ∈=),,(21, ,2112⎪⎭⎫ ⎝⎛=∑=ni i i x a X是nC 中的向量范数.证明:因为 (1),02112≥⎪⎭⎫⎝⎛=∑=ni i ix a X 且00=⇔=X X ;(2)X k x a k x a k kx a kX ni i i ni i i ni i i =⎪⎭⎫⎝⎛=⎪⎭⎫ ⎝⎛=⎪⎭⎫⎝⎛=∑∑∑===2112211222112;(3)关于nT n C y y y Y ∈=),,(21, ,T n n y x y x y x Y X ),,(2211+++=+, ,则21212122)(2Y X Y X y a x a y x a YX ni ii ni ii ni ii i +=++≤+=+∑∑∑===故Y X Y X +≤+.因此2112⎪⎭⎫⎝⎛=∑=ni i i x a X 是nC 中的向量范数. 12.证明:ij nj i a n A ≤≤=,1m ax是矩阵n n ij a A ⨯=)(的范数,而且与向量的1-范数是相容的.证明:因为(1) 0m ax ,1≥=≤≤ij nj i a n A ,且O A =⇔0=A ;(2) A k a n k ka n kA ij nj i ij nj i =≥=≤≤≤≤,1,1m ax m ax ;(3) B A b n a n b a n B A ij nj i ij nj i ij ij nj i +=+≥+=+≤≤≤≤≤≤,1,1,1m ax m ax m ax(4)设Tn x x x X ),,,(21 =,那么T nj j nj n j j j n j j j x a x a x a AX ),,,(11211∑∑∑==== ,故∑∑∑===+++=nj j njnj j jnj j jx ax ax aAX 11111∑∑∑=≤≤=≤≤=≤≤+++≤nj j nj nj nj j j nj nj jjnj x a x a xa 11121111max max max11,1max X A xa n nj jijnj i =≤∑=≤≤因此ij nj i a n A ≤≤=,1m ax 是与向量的1-范数相容的矩阵范数.13.设nn CA ⨯∈,且A 可逆,证明:11--≥AA .证明:由于I AA =-1,1=I ,则111--≤==A A AA I ,故11--≥AA .14.设nn CA ⨯∈,且,1<A 证明:A I -可逆,而且有(1)AA I -≤--11)(1;(2)AA I A I -≤---1)(1.证明:(1)由于A A I I A I 11)()(---+=-,故A A I I A A I I A I 111)()()(----+≤-+≤-,即 AA I -≤--11)(1.(2)因为A I A I =-+)(,两边右乘1)(-+A I ,可得11)()(--+=+-A I A A I I ,左乘A ,整理得11)()(--+-=+A I AA A A I A ,则111)()()(---++≤+-=+A I A A A A I AA A A I A ,即 AA I A I -≤---1)(1.15.设C l k CB A nn ∈∈⨯,,,证明:(1)Al k klkA ee e )(+=,专门地A A e e --=1)(;(2)当BA AB =时,BA AB BA e e e e e +==;(3)A e Ae e dtd At At At==; (4)当BA AB =时,B A B A B A sin cos cos sin )sin(±=±. 证明:(1)∑∑∑∞==-∞=+⎥⎦⎤⎢⎣⎡=+=000)()()(!1!)(n n m m n m m n n n n Al k lA kA C n n A l k e∑∑∑∑∞=∞=∞=∞=+++=+=-0000)()(!!)!()!(1)()()!(1m l l m m l lm m m l lA kA m l m l m l lA kA C m l l m nlA kA l l m m m l l m e e kA l kA m lA kA m l =⎪⎭⎫ ⎝⎛⎪⎭⎫ ⎝⎛==∑∑∑∑∞=∞=∞=∞=0000)(!1)(!1)()(!!1.又因为A A A A O e e e e I --+===)(,故A A e e --=1)(.(2)当BA AB =时,二项式公式∑===+nm mm n m n nB AC B A 0)(成立,故∑∑∑∞==-∞=+⎪⎭⎫ ⎝⎛=+=000!1)(!1n n m m m n m n n nBA B A C n B A n e∑∑∑∑∞=∞=∞=∞=+=+=-0000!!1)!(1m l m l m l ml m m l B A m l B A C m l l m nBA m m l l e eB m A l =⎪⎭⎫ ⎝⎛⎪⎭⎫ ⎝⎛=∑∑∞=∞=00!1!1 同理,有A B l l m m BA e e A lB m e=⎪⎭⎫⎝⎛⎪⎭⎫ ⎝⎛=∑∑∞=∞=+00!1!1, 故B A A B B A e e e e e +==.(3)由于幂级数∑∞=0!1n nn tA n 对给定的矩阵A ,和任意的t 都是绝对收敛的,且对任意的t 都是一致收敛的,因此科可对此幂级数逐项求导,那么A l ll n n n n n n At Ae l t A A n t A t A n dt d e dt d ==-=⎪⎭⎫ ⎝⎛=∑∑∑∞=∞=-∞=0110!)!1(!1, 同理,有A e A l t A e dt d Al ll At =⎪⎪⎭⎫ ⎝⎛=∑∞=0! 故A e Ae e dtd At At At==. (1) 因为-+-++=432!41!31!21A iA A iA I e iA )!51!31()!41!21(5342 -+-+-+-=A A A i A A IA i A sin cos +=故)(21sin iA iAe e iA --=. 又当BA AB =时,B A A B B A e e e e e +==,则()()iB iA iBiA B A i B A i e e e e i e e i B A --+-+-=-=+2121)sin()()( )]sin )(cos sin (cos )sin )(cos sin [(cos 21B i B A i A B i B A i A i---++= B A B A sin cos cos sin += 同理,可得B A B A B A sin cos cos sin )sin(-=-16.求以下三类矩阵的矩阵函数2,sin ,cos Ae A A(1)当A 为幂等矩阵(A A =2)时; (2)当A 为对合矩阵(I A =2)时; (3)当A 为幂零矩阵(O A =2)时.解:(1) A A =2,设矩阵A 的秩为r ,那么A 的特点值为1或0, A 可对角化为J O O O I AP P r =⎥⎦⎤⎢⎣⎡=-1, 则11001sin 1sin sin sin --⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡==P P JP P AA PJP )1(sin )1(sin 1==-,11111cos 1cos cos cos --⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡==P P JP P A110011cos 11cos 1111--⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡--+⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=P P P PAI PJP I )11(cos )11(cos 1-+=-+=-111122--⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡==P e e P P Pe e J A1100111111--⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡--+⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=P e e P P PA e I PJP e I )1()1(1-+=-+=-(2) 当I A =2时,矩阵A 也可对角化,A 的特点值为1或1-, A 可对角化为J AP P =⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡--=-11111 ,其中1有m 个.则111sin 1sin 1sin 1sin sin sin --⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡--==P P JP P AAPJP )1(sin )1(sin 1==-111cos 1cos 1cos 1cos cos cos --⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡==P P JP P A I )1(cos =eI P e e e e P P Pe e J A =⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡==--1122(3)当O A =2时, A 的特点值均为0,那么存在可逆矩阵P ,使得11,--==PJP A J AP P ,其中⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=m J J J 1,又O A =2,那么O P PJ A ==-122,于是O J J J m =⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=2212故Jordan 块k J 的阶数最多为2,不妨设0=k J ),,1(r k =,B J k =⎥⎦⎤⎢⎣⎡=0010),,1(m r k +=,即 ⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=B B J 0则1=k iJ e ,1=-k iJ e ),,1(r k =;⎥⎦⎤⎢⎣⎡=101i e k iJ ,⎥⎦⎤⎢⎣⎡-=-101i e k iJ ),,1(m r k +=.故=--k k iJ iJ e e 0),,1(r k =,B ii e e k k iJ iJ 210020=⎥⎦⎤⎢⎣⎡=--),,1(m r k +=, 则2=+-k k iJ iJ e e ),,1(r k =,I e e k k iJ iJ 22002=⎥⎦⎤⎢⎣⎡=+-),,1(m r k +=, 因此J iB B i e e iJiJ 210021=⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=-- ,Ie e iJiJ 22222=⎥⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎢⎣⎡=+- , 因此A PJP i i P e e P i e e i A iJ iJ iA iA =⋅=-=-=----11)2(21)(21)(21sin , I PIP P e e P e e A iJ iJ iA iA =⋅=+=+=----11221)(21)(21cos ,I I e e O A ==2.17.假设矩阵A 的特点值的实部全为负,那么O e At t =+∞→lim .证明: 设A 的特点值为0,1,<-=+=i i i i a j j b a λ,那么存在可逆矩阵P ,使得11,--==PJP A J AP P ,其中⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=m J J J 1,ini ii J ⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎣⎡=λλ11则1121--⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎣⎡==P e e e P PPe et J tJ t J Jt Atm,其中⎥⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎢⎣⎡-=-t tt t t i n tt tJ e tete e e n t tee ei i 11111111)!1(λλλλλλλ又)sin (cos lim lim lim t b j t b e e e i i t a t t jb t a t t t i i i i +==∞→+∞→∞→λ,且0<i a ,故0lim =∞→tt i eλ,因此O e t J t i =∞→lim ,那么O e At t =+∞→lim .18.计算Ate 和At sin ,其中:(1)⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=110010002A ; (2)⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡-=010101010A ; (3)⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡---=6116100010A .解:(1)设,21=J ⎥⎦⎤⎢⎣⎡=11012J ,那么⎥⎦⎤⎢⎣⎡=21J JA . 由于⎥⎦⎤⎢⎣⎡=t J tAt e e e 22,⎥⎦⎤⎢⎣⎡=t J t At 2sin 2sin sin , 且⎥⎦⎤⎢⎣⎡=t t t tJ e tee e02,⎥⎦⎤⎢⎣⎡=t t t tt J sin cos 0sin sin 2, 则⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=t tt tAte te e e e 000002,⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=t t t t t At sin cos 00sin 0002sin sin .(2)该矩阵的特点多项式为,11101)(3λλλλλϕ=---=最小多项式为3)(λλ=m .19.计算以下矩阵函数:(1)⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=221131122A ,求100A ; (2)⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡---=735946524A ,求Ae ;(3)⎥⎦⎤⎢⎣⎡-=4410A ,求4arcsin A; (4)⎥⎦⎤⎢⎣⎡=48816A ,求1)(-+A I 及21A 20.证明:I A A =+22cos sin ,A iI A e e =+π2,其中A 为任意方阵.证明:(1) 因为)(21sin iA iA e e i A --=,)(21cos iA iA e e A -+=,故)2(41)(41sin 2222I e e e e A iA iA iA iA -+-=--=--, )2(41)(41cos 2222I e e e e A iA iA iA iA ++=+=--,则I A A =+22cos sin .(2)因为矩阵iI π2的特点值均为i π2,故存在可逆矩阵P ,使得I P P P e e P e i i iI=⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=⎥⎥⎥⎦⎤⎢⎢⎢⎣⎡=--1122211 πππ则A A iI A iI A e I e e e e ===+ππ2221.假设A 为反实对称(反Hermite )矩阵,那么Ae 为实正交(酉)矩阵. 证明: 因为∑∞==0!k k A k A e ,又∑∑===⎪⎪⎭⎫ ⎝⎛nk k n k k k A k A 0**0!)(!. 故**)(A A e e =.当A 为反实对称,即A A T-=时,I e e e e e e e O A A A A A T A T====-)(,故Ae 为实正交矩阵;当A 为反Hermite 矩阵,即A A -=*时,I e e e e e e e O A A A A A A ====-**)(,故Ae 为酉矩阵.22.假设A 为Hermite 矩阵,那么Aie 是酉矩阵,并说明当1=n 时此结论的意义.证明:因为A A =*,故Ai Ai Ai e ee -==*)(*)(,则I e e e e Ai Ai Ai Ai ==-*)(,故Aie 是酉矩阵.当A 为一阶Hermite 矩阵时, A 为一实数,设a A =,那么上述命题为1=-ai ai e e23.将以下矩阵函数表示成矩阵幂级数,并说明对A 的限制: (1)shA ,(2))ln(A I +,(3)A arctan解:(1) ∑∞=++=012)!12(1n n A n shA , n n C A ⨯∈∀; (2) ∑∞=--=+111)1(4)ln(n nn A nA I ,1<A ; (3) ∑∞=++-=112121)1(arctan n n nA n A ,1<A . 24.设nn C A ⨯∈,证明:(1))(A tr Ae e=,(2)AAe e ≤.证明:(1)设11,--==PJP A J AP P ,其中J 为假设当标准形,那么1121--⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎣⎡==P e e e P PPe e m J J J J A,其中⎥⎥⎥⎥⎥⎥⎦⎤⎢⎢⎢⎢⎢⎢⎣⎡=111111λλλe e e e iJ, 则mJ J J JJAe e e e Pe P e211===-trA J J J e e e e e n m ===++λλ 121.(2)设∑==Nk kN k A S 0!,那么∑∑∑===≤≤=Nk kN k k Nk k NA k A k k A S 000!1!1!, 因为∑∞==!k kAk A e ,对上式两边取极限,得 Ak kAeA k e≤≤∑∞=0!1.25.设nn CA ⨯∈,且A 可逆,假设λ是A 的任一特点值,那么2211A A ≤≤-λ.证明:因为2)(A A =≤ρλ,故2A ≤λ.又对任意的nC X ∈,有2212122AX A AX A IXX--≤==,因此2212AX AX ≤-.设α是矩阵A 的特点值λ对应的特点向量,即λαα=A ,那么222212αλλααα==≤-A A,故有λ≤-211A .因此2211A A ≤≤-λ.。

南航双语矩阵论matrixtheory第五章部分习题参考答案

南航双语矩阵论matrixtheory第五章部分习题参考答案

第五章部分习题参考答案#2. Find determinant divisors and elementary divisors of each of the following matrices.(a) 1000100015432λλλλ-⎛⎫ ⎪-⎪ ⎪- ⎪+⎝⎭ (b)001010100000λλλλ⎛⎫⎪ ⎪ ⎪ ⎪⎝⎭Solution(a ) 100010()0015432A λλλλλ-⎛⎫ ⎪- ⎪= ⎪- ⎪+⎝⎭det (())A λ4322345λλλλ=++++100det 10101λλ-⎛⎫⎪-=- ⎪ ⎪-⎝⎭. Hence, the determinant divisors are 123()()()1D D D λλλ===,4324()2345D λλλλλ=++++. Invariant divisor are 123()()()1d d d λλλ===,4324()2345d λλλλλ=++++Unfortunately, it is not easy to factorize 4324()2345d λλλλλ=++++ by hand. With the help of Maple or Matlab, we can see that ()A λ has four distinct linear elementary divisors. (b) 44()D λλ=, 123()()()1D D D λλλ===. There is a unique elementary divisor 4λ #3. Let11a a A a ⎛⎫ ⎪ ⎪= ⎪ ⎪⎝⎭ , a a B a εε⎛⎫ ⎪⎪= ⎪ ⎪⎝⎭ be n n ⨯ matrices, where 0ε≠. Show that A and B are similar.Proof The Smith normal forms of both I A λ- and I B λ-are11()n a λ⎛⎫ ⎪⎪ ⎪ ⎪-⎝⎭. A and B have the same set of elementary divisors. Hence they are similar to each other. #4. Let11a a A a ⎛⎫ ⎪ ⎪= ⎪ ⎪⎝⎭ , 11a a B a ε⎛⎫ ⎪⎪= ⎪ ⎪⎝⎭be n n ⨯ matrices, where 0ε≠. Show that A and B are NOT similar. ProofThe determinant of I A λ- is ()n a λ- . The determinant of I B λ- is ()n a λε--. A and B have distinct characteristic polynomials. Hence, they are not similar.#11. How many possible Jordan forms are there for a 66⨯ complex matrix with characteristic polynomial 42(2)(1)x x +-?Solution The possibilities for the sets of elementary divisors are { 42(2),(1)x x +-}, {4(2),(1),(1)x x x +--}{32(2),(2),(1)x x x ++-}, {3(2),(2),(1),(1)x x x x ++--} {222(2),(2),(1)x x x ++-}, {22(2),(2),(1),(1)x x x x ++--},{22(2),(2),(2),(1)x x x x +++-}, {2(2),(2),(2),(1),(1)x x x x x +++--}{2(2),(2),(2),(2),(1)x x x x x ++++-}, {(2),(2),(2),(2),(1),(1)x x x x x x ++++--}. For each set of elementary divisors, there is a Jordan canonical form up to similarity. There are 10 Jordan canonical forms up to similarity.#12. Classify up to similarity all 33⨯ complex matrices A such that 3A I =. Solution An annihilating polynomial of A is 321(1)()()x x x x ωω-=---, where ω A is diagonalizable.The possibilities for the minimal polynomial of A are1x -, x ω-, 2x ω-;(1x -)(x ω-), (x ω-)(2x ω-), (1x -)(2x ω-);2(1)()()x x x ωω---Up to similarity, all 33⨯ complex matrices A are100010001⎛⎫ ⎪ ⎪ ⎪⎝⎭, 000000ωωω⎛⎫⎪ ⎪ ⎪⎝⎭, 222000000ωωω⎛⎫ ⎪ ⎪ ⎪⎝⎭; 10001000ω⎛⎫⎪ ⎪ ⎪⎝⎭, 1000000ωω⎛⎫ ⎪ ⎪ ⎪⎝⎭; 22000000ωωω⎛⎫ ⎪⎪ ⎪⎝⎭, 2000000ωωω⎛⎫ ⎪ ⎪ ⎪⎝⎭;221000000ωω⎛⎫⎪ ⎪ ⎪⎝⎭,210001000ω⎛⎫⎪ ⎪ ⎪⎝⎭21000000ωω⎛⎫ ⎪ ⎪ ⎪⎝⎭#14. If N is a nilpotent (幂零的) 33⨯ matrix over C , prove that 21128A I N N =+- satisfies2A I N =+, i.e., A is a square root of I N +. Use the binomial series for 1/2(1)t + to obtain asimilar formula for a square root of I N +, where N is any nilpotent n n ⨯ matrix over C .Use the result above to prove that if c is a non-zero complex number and N is a nilpotent complex matrix, then cI N +has a square root. Now use the Jordan form to prove that every non-singular complex n n ⨯ matrix has a square root.Solution If N is an n n ⨯ matrix and k N O =, then k x is an annihilating polynomial for N . The minimal polynomial of N must be of the form p x , where p n ≤ and p k ≤ since the minimal polynomial of a matrix divides its characteristic polynomial. Thus, n N O =.(1) If N is a nilpotent 33⨯ matrix, then 3N O =. By straightforward computation, we can verify that 2A I N =+.(2) If N is an n n ⨯ nilpotent matrix, n N O =.1/22111111(1)(1)((1)1)122222(1)122!(1)!n n t t t t n -----++=+++++- 1/22111111(1)(1)((1)1)122222()22!(1)!n n I N I N N N n -----++=++++-(3) Since1N c is a nilpotent matrix, 1I N c + has a square root 1/21()I N c+. cI N + has a square root 1/21/21()c I N c+.(4) Suppose that 12121()0()000()r d d d r J J P AP J J λλλ-⎛⎫ ⎪⎪==⎪ ⎪ ⎪⎝⎭. Then each ()k d k J λ has asquare root 1/2()k d k J λ since ()k d k J λ is of the form k I N λ+, where 0k λ≠ because A is nonsingular and N is nilpotent.Let 121/211/2211/2()000()000()r d d d r J J B P P J λλλ-⎛⎫⎪⎪=⎪ ⎪⎪⎝⎭, then 2B A =. Hence, A has a squareroot.#20. Prove that the minimal polynomial of a matrix is equal to the characteristic polynomial if andonly if the elementary divisors are relatively prime in pairs.Proof Suppose that a Jordan canonical form of A is1212()000()000()r d d d r J J J J λλλ⎛⎫⎪ ⎪=⎪ ⎪ ⎪⎝⎭(where 12,,,r λλλ are not necessarily distinct. Each ()i d i J λ is a Jordan block.)The minimal polynomial of A is the same as that of J . The characteristic polynomial of A is the same as that of J . The elementary divisors of A are 11()d λλ-, , ()rd r λλ-The minimal polynomial of ()i d i J λ is ()i d i λλ-. The minimal polynomial of J is the least common multiple (最小公倍式) of 11()d λλ-, , ()rd r λλ-. The characteristicpolynomial of J is 1212()()()()rd d d r p λλλλλλλ=--- .The least common divisor of 11()d λλ-, , ()rd r λλ- is equal to the product of11()d λλ-, , ()r d r λλ- if and only if ()j dj λλ-and ()k d k λλ-are relatively prime forj k ≠. Thus the minimal polynomial of a matrix is equal to the characteristic polynomial ifand only if the elementary divisors are relatively prime in pairs.。

南航矩阵论课后习题答案

南航矩阵论课后习题答案

南航矩阵论课后习题答案南航矩阵论课后习题答案矩阵论是数学中的一个重要分支,广泛应用于各个领域,包括物理学、工程学、计算机科学等等。

南航的矩阵论课程是培养学生数学思维和解决实际问题的重要环节。

在课后习题中,学生需要运用所学的矩阵理论知识,解答各种问题。

下面是南航矩阵论课后习题的一些答案和解析。

1. 已知矩阵A = [1 2 3; 4 5 6; 7 8 9],求A的逆矩阵。

解析:要求一个矩阵的逆矩阵,需要先判断该矩阵是否可逆。

一个矩阵可逆的充要条件是其行列式不为零。

计算矩阵A的行列式,得到det(A) = -3。

因此,矩阵A可逆。

接下来,我们可以使用伴随矩阵法求解逆矩阵。

首先,计算矩阵A的伴随矩阵Adj(A),然后将其除以行列式的值,即可得到逆矩阵。

计算得到A的伴随矩阵为Adj(A) = [-3 6 -3; 6 -12 6; -3 6 -3]。

最后,将伴随矩阵除以行列式的值,即可得到矩阵A的逆矩阵A^-1 = [-1 2 -1; 2 -4 2; -1 2 -1]。

2. 已知矩阵A = [2 1; 3 4],求A的特征值和特征向量。

解析:要求一个矩阵的特征值和特征向量,需要先求解其特征方程。

特征方程的形式为|A - λI| = 0,其中A为给定矩阵,λ为特征值,I为单位矩阵。

计算得到特征方程为|(2-λ) 1; 3 (4-λ)| = (2-λ)(4-λ) - 3 = λ^2 - 6λ + 5 = 0。

解这个二次方程,得到特征值λ1 = 1,λ2 = 5。

接下来,我们可以求解对应于每个特征值的特征向量。

将特征值代入(A - λI)x = 0,即可求解出特征向量。

对于特征值λ1 = 1,解得特征向量x1 = [1; -1];对于特征值λ2 = 5,解得特征向量x2 = [1; 3]。

3. 已知矩阵A = [1 2; 3 4],求A的奇异值分解。

解析:奇异值分解是将一个矩阵分解为三个矩阵的乘积:A = UΣV^T,其中U和V是正交矩阵,Σ是对角矩阵。

最新南航矩阵论研究生试卷及答案

最新南航矩阵论研究生试卷及答案
(1)求系数矩阵 的满秩分解;
(2)求广义逆矩阵 ;
(3)求该线性方程组的极小最小二乘解.
在上海,随着轨道交通的发展,地铁商铺应运而生,并且在重要的商业圈已经形成一定的气候,投资经营地铁商铺逐渐成为一大热门。在人民广场地下“的美”购物中心,有一家DIY自制饰品店---“碧芝自制饰品店”。解答:(1)矩阵 , 的满秩分解为
(1)若对任意 ,有 则 可逆;
我们大学生没有固定的经济来源,但我们也不乏缺少潮流时尚的理念,没有哪个女生是不喜欢琳琅满目的小饰品,珠光宝气、穿金戴银便是时尚的时代早已被推出轨道,简洁、个性化的饰品成为现代时尚女性的钟爱。因此饰品这一行总是吸引很多投资者的目光。然而我们女生更注重的是感性消费,我们的消费欲望往往建立在潮流、时尚和产品的新颖性上,所以要想在饰品行业有立足之地,又尚未具备雄厚的资金条件的话,就有必要与传统首饰区别开来,自制饰品就是近一两年来沿海城市最新流行的一种。(2)若 都是Hermite正定矩阵,则 的特征值均为正数;
南京航空航天大学2012级硕士研究生
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2012 ~ 2013学年第1学期《矩阵论》课程考试A卷
考试日期:2013年1月15日课程编号:A080001命题教师:阅卷教师:
学院专业学号姓名成绩
一、(20分)设 是 的一个线性子空间,对任意 ,定义: ,其中 .
(1)求 的一组基和维数;
(2)对任意 ,定义:
(2)因为 是相容范数,且 ,则 在收敛半径内,因此级数收敛.……………(5分)
(3) .……………(5分)
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南京航空航天大学研究生课程《矩阵论》内容总结与习题选讲

南京航空航天大学研究生课程《矩阵论》内容总结与习题选讲

《矩阵论》复习提纲与习题选讲Chapter1 线性空间和内积空间内容总结:z 线性空间的定义、基和维数;z 一个向量在一组基下的坐标;z 线性子空间的定义与判断;z 子空间的交z 内积的定义;z 内积空间的定义;z 向量的长度、距离和正交的概念;z Gram-Schmidt 标准正交化过程;z 标准正交基。

习题选讲:1、设表示实数域3]x [R R 上次数小于3的多项式再添上零多项式构成 的线性空间(按通常多项式的加法和数与多项式的乘法)。

(1) 求的维数;并写出的一组基;求在所取基下的坐标;3]x [R 3]x [R 221x x ++ (2) 在中定义3]x [R , ∫−=11)()(),(dx x g x f g f n x R x g x f ][)(),(∈ 证明:上述代数运算是内积;求出的一组标准正交基;3][x R (3)求与之间的距离;221x x ++2x 2x 1+−(4)证明:是的子空间;2][x R 3]x [R (5)写出2[][]3R x R x ∩的维数和一组基;二、 设22R ×是实数域R 上全体22×实矩阵构成的线性空间(按通常矩阵的加 法和数与矩阵的乘法)。

(1) 求22R ×的维数,并写出其一组基;(2) 在(1)所取基下的坐标; ⎥⎦⎤⎢⎣⎡−−3111(3) 设W 是实数域R 上全体22×实对称矩阵构成的线性空间(按通常矩阵的加法和数与矩阵的乘法)。

证明:W 是22R ×的子空间;并写出W 的维数和一组基;(4) 在W 中定义内积, )A B (tr )B ,A (T =W B ,A ∈求出W 的一组标准正交基;(5)求与之间的距离; ⎥⎦⎤⎢⎣⎡0331⎥⎦⎤⎢⎣⎡−1221 (6)设V 是实数域R 上全体22×实上三角矩阵构成的线性空间(按通常矩阵的加法和数与矩阵的乘法)。

证明:V 也是22R ×的子空间;并写出V 的维数和一组基;(7)写出子空间的一组基和维数。

南航07-14矩阵论试卷

南航07-14矩阵论试卷

南航07-14矩阵论试卷南京航空航天大学07-14硕士研究生矩阵论试题2007 ~ 2008学年《矩阵论》课程考试A 卷一、(20分)设矩阵-----=111322211A ,(1)求A 的特征多项式和A 的全部特征值;(2)求A 的行列式因子、不变因子和初等因子;(3)求A 的最小多项式,并计算I A A 236-+;(4)写出A 的Jordan 标准形。

二、(20分)设22?R 是实数域R 上全体22?实矩阵构成的线性空间(按通常矩阵的加法和数与矩阵的乘法)。

(1)求22?R的维数,并写出其一组基;(2)设W 是全体22?实对称矩阵的集合,证明:W 是22?R的子空间,并写出W 的维数和一组基;(3)在W 中定义内积W B A BA tr B A ∈=,),(),(其中,求出W 的一组标准正交基;(4)给出22?R 上的线性变换T :22,)(?∈?+=R A A A A T T写出线性变换T 在(1)中所取基下的矩阵,并求T 的核)(T Ker 和值域)(T R 。

三、(20分)(1)设-=121312A ,求1A ,2A ,∞A ,F A ;(2)设nn ij C a A ?∈=)(,令ijji a n A ,*max ?=,证明:*是n n C ?上的矩阵范数并说明具有相容性;(3)证明:*2*1A A A n ≤≤。

四、(20分)已知矩阵-=100100011111A ,向量=2112b ,(1)求矩阵A 的QR 分解;(2)计算+A ;(3)用广义逆判断方程组b Ax =是否相容?若相容,求其通解;若不相容,求其极小最小二乘解。

五、(20分)(1)设矩阵=????? ??=15.025.011210,2223235t t B t t A ,其中t 为实数,问当t 满足什么条件时, B A >成立?(2)设n 阶Hermite 矩阵022121211>=A A A A A H,其中k k C A ?∈11,证明:0,012111122211>->-A A A A A H。

南航双语矩阵论-matrix-theory第三章部分题解精选全文

可编辑修改精选全文完整版Solution Key to Some Exercises in Chapter 3 #5. Determine the kernel and range of each of the following linear transformations on 2P(a) (())'()p x xp x σ=(b) (())()'()p x p x p x σ=- (c) (())(0)(1)p x p x p σ=+Solution (a) Let ()p x ax b =+. (())p x ax σ=.(())0p x σ= if and only if 0ax = if and only if 0a =. Thus, ker(){|}b b R σ=∈The range of σis 2()P σ={|}ax a R ∈ (b) Let ()p x ax b =+. (())p x ax b a σ=+-.(())0p x σ= if and only if 0ax b a +-= if and only if 0a =and 0b =. Thus, ker(){0}σ=The range of σis 2()P σ=2{|,}P ax b a a b R +-∈=(c) Let ()p x ax b =+. (())p x bx a b σ=++.(())0p x σ= if and only if 0bx a b ++= if and only if 0a =and 0b =. Thus, ker(){0}σ=The range of σis 2()P σ=2{|,}P bx a b a b R ++∈= 备注: 映射的核以及映射的像都是集合,应该以集合的记号来表达或者用文字来叙述. #7. Let be the linear mapping that maps 2P into 2R defined by10()(())(0)p x dx p x p σ⎛⎫⎪= ⎪⎝⎭⎰ Find a matrix A such that()x A ασαββ⎛⎫+= ⎪⎝⎭.Solution1(1)1σ⎛⎫= ⎪⎝⎭ 1/2()0x σ⎛⎫= ⎪⎝⎭11/211/2()1010x ασαβαββ⎛⎫⎛⎫⎛⎫⎛⎫+=+= ⎪ ⎪⎪⎪⎝⎭⎝⎭⎝⎭⎝⎭Hence, 11/210A ⎛⎫= ⎪⎝⎭#10. Let σ be the transformation on 3P defined by(())'()"()p x xp x p x σ=+a) Find the matrix A representing σ with respect to 2[1,,]x x b) Find the matrix B representing σ with respect to 2[1,,1]x x + c) Find the matrix S such that 1B S AS -=d) If 2012()(1)p x a a x a x =+++, calculate (())n p x σ.Solution (a) (1)0σ= ()x x σ=22()22x x σ=+002010002A ⎛⎫⎪= ⎪ ⎪⎝⎭(b) (1)0σ=()x x σ=22(1)2(1)x x σ+=+000010002B ⎛⎫⎪= ⎪ ⎪⎝⎭(c)2[1,,1]x x +2[1,,]x x =101010001⎛⎫⎪⎪ ⎪⎝⎭The transition matrix from 2[1,,]x x to 2[1,,1]x x + is101010001S ⎛⎫ ⎪= ⎪ ⎪⎝⎭, 1B S AS -=(d) 2201212((1))2(1)n n a a x a x a x a x σ+++=++#11. Let A and B be n n ⨯ matrices. Show that if A is similar to B then there exist n n ⨯ matrices S and T , with S nonsingular, such thatA ST =andB TS =.Proof There exists a nonsingular matrix P such that 1A P BP -=. Let 1S P -=, T BP =. Then A ST =and B TS =.#12. Let σ be a linear transformation on the vector space V of dimension n . If there exist a vector v such that 1()v 0n σ-≠ and ()v 0n σ=, show that(a) 1,(),,()v v v n σσ- are linearly independent.(b) there exists a basis E for V such that the matrix representing σ with respect to the basis E is000010000010⎛⎫⎪⎪⎪⎪⎝⎭Proof(a) Suppose that1011()()v v v 0n n k k k σσ--+++= Then 11011(()())v v v 0n n n k k k σσσ---+++=That is, 12210110()()())()v v v v 0n n n n n k k k k σσσσ----+++==Thus, 0k must be zero since 1()v 0n σ-≠. 211111(()())()v v v 0n n n n k k k σσσσ----++==This will imply that 1k must be zero since 1()v 0n σ-≠.By repeating the process above, we obtain that 011,,,n k k k - must be all zero. Thisproves that1,(),,()v v v n σσ- are linearly independent.(b) Since 1,(),,()v v v n σσ- are n linearly independent, they form a basis for V .Denote 112,(),,()εv εv εv n n σσ-=== 12()εεσ= 23()εεσ= …….1()εεn n σ-= ()ε0n σ=12[(),(),,()]εεεn σσσ121[,,,,]εεεεn n -=000010000010⎛⎫⎪⎪⎪⎪⎝⎭#13. If A is a nonzero square matrix and k A O =for some positive integer k , show that A can not be similar to a diagonal matrix.Proof Suppose that A is similar to a diagonal matrix 12diag(,,,)n λλλ. Then for each i , there exists a nonzero vector x i such that x x i i i A λ= x x x 0k k i i i i i A λλ=== since k A O =.This will imply that 0i λ= for 1,2,,i n =. Thus, matrix A is similar to the zero matrix. Therefore, A O =since a matrix that is similar to the zero matrix must be the zero matrix, whichcontradicts the assumption.This contradiction shows that A can not be similar to a diagonal matrix. OrIf 112diag(,,,)n A P P λλλ-= then 112diag(,,,)k k k k n A P P λλλ-=. k A O = implies that 0i λ= for 1,2,,i n =. Hence, B O =. This will imply that A O =.Contradiction!。

矩阵论第三章答案

d1 (λ ) = L = d n −1 (λ ) = 1 , d n (λ ) = (λ − a )
n
因此初等因子只有一个,即有 (λ − a )n .
11. 证:
A( λ )与 B( λ )相抵当且仅当它们有相同的不变因
子,当且仅当它们的各阶行列式因子相同.
1 1 ⎤ ⎡λ − 2 ⎢ 12. 解 : ( 1 ) 因 为 λI − A = ⎢ − 2 λ + 1 2 ⎥ ⎥ 的初等因子为 ⎢ − 1 λ − 2⎥ ⎣ 1 ⎦
0 0 ⎤ r2 − (− 1)r3 ⎡1 0 0 ⎤ c 2 − (2λ − 1)c1 ⎡1 ⎢0 ⎥ ⎢ 2 λ − λ ⎥ ⎯⎯ ⎯ λ2 ⎥ ⎯⎯ ⎯ ⎯→ ⎢ ⎯→ ⎢0 λ ⎥ 2 2 2 ⎥ ⎢ ⎥ c3 + (− λ )c1 ⎢ ( ) r + 1 − λ r 0 λ − λ − λ − λ 0 0 − λ − λ 3 2 ⎣ ⎦ ⎣ ⎦
2. 解 : ( 1)因为 A 的特征矩阵为
⎡λ + 1 ⎤ ⎢ ⎥ λ+2 ⎢ ⎥ A(λ ) = λI − A = ⎢ ⎥ λ −1 ⎢ ⎥ λ − 2⎦ ⎣
所以 A( λ )的行列式因子为
⎡1⎤ A=⎢ ⎥ ⎣1⎦
不变因子为
d 1 (λ ) = D1 (λ ) = 1, d 4 (λ ) = D4 (λ ) D3 (λ ) d 2 (λ ) = d 3 (λ ) = 1,
10. 解:
因为 A(λ ) = (λ − a )n ,所以 Dn (λ ) = (λ − a )n ,又因
c1 λ − a c2 O
O
= c1c 2 L c n −1 ≠ 0 ,
λ − a c n −1

南航双语矩阵论matrix theory第4章部分习题参考答案


)
If i is a root of p( ) 0 , then p(i ) 0 . We obtain that eigenvalue of C T with eigenvector x (1, i ,, in 2 , in 1 )T .
Exercise 16
Let be an orthogonal transformation on a Euclidean space V (an inner product space over the real number field). If W is a -invariant subspace of V, show that the orthogonal complement of W is also -invariant. Proof Let V W W , where W is -invariant. Let {u1 , u2 ,, uk } be an orthonormal basis for
0 1 T C x 0 0 0 0 1 0 0 0 0 0 0 an 0 an 1 0 an 2 1 a1
T
i i 1 2 2 i i i n2 n 1 n 1 i i i n 1 n n 1 a a a p ( i n i n 1 i 1 i i
C T x i x . Then i is an
(b) If p( ) has n distinct roots, then all roots of p( ) are eigenvalues of C T . We obtain that the characteristic polynomial of C T and p( ) have the same n distinct roots. And also they have the same degree and the same leading coefficient. Hence, the characteristic polynomial of C T is the same as p( ) . Since C and C T have the same characteristic polynomial, we know that p( ) is the characteristic polynomial of C.

矩阵论第3章3-4节

在一个点 x0 [a, b], 使
P( x0 ) f ( x0 ) ,
所以说 P (x ) 的偏差点总是存在的.
4
定理5
P( x) H n 是 f C[a, b] 的最佳逼近多项式
的充分必要条件是 P (x ) 在 [a, b] 上至少有n 2 个轮流为“正”、 “负”的偏差点, 即有 n 2个点 a x1 x2 xn 2 b ,

n b I 2 ( x)[ a j j ( x) f ( x)] k ( x)dx a ak j 0
(k 0,1,, n),
21
于是有
(
j 0
n
k
( x), j ( x)) a j ( f ( x), k ( x)) (k 0,1, , n). (4.3)
En inf {( f , Pn )} inf max f ( x) Pn ( x) , (3.2)
Pn H n
Pn H n a x b
则称之为 f (x) 在 [a, b]上的最小偏差.
2
定义8 假定 f C[a, b], 若存在 Pn* ( x) H n 使得
且点 xk cos
k π(k 0,1, , n) 是 Tn ( x)的切比雪夫交错点组, n
8
由定理5可知,区间 [1, 1] 上 x n 在 H n 1 中最佳逼近多项式
* 为 Pn1 ( x), 即 n (x) 是与零的偏差最小的多项式.定理得证.
9
例3 求 f ( x) 2 x3 x 2 2 x 1 在 [1, 1]上的最佳2次逼 近多项式. 解 由题意,所求最佳逼近多项式 P2* ( x) 应满足
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Solution Key to Some Exercises in Chapter 3 #5. Determine the kernel and range of each of the following linear transformations on 2P
(a) (())'()p x xp x σ=
(b) (())()'()p x p x p x σ=-
(c) (())(0)(1)p x p x p σ=+
Solution (a) Let ()p x ax b =+. (())p x ax σ=.
(())0p x σ= if and only if 0ax = if and only if 0a =. Thus, ker(){|}b b R σ=∈
The range of σis 2()P σ={|}ax a R ∈
(b) Let ()p x ax b =+. (())p x ax b a σ=+-.
(())0p x σ= if and only if 0ax b a +-= if and only if 0a =and 0b =.
Thus, ker(){0}σ=
The range of σis 2()P σ=2{|,}P ax b a a b R +-∈=
(c) Let ()p x ax b =+. (())p x bx a b σ=++.
(())0p x σ= if and only if 0bx a b ++= if and only if 0a =and 0b =.
Thus, ker(){0}σ=
The range of σis 2()P σ=2{|,}P bx a b a b R ++∈=
备注: 映射的核以及映射的像都是集合,应该以集合的记号来表达或者用文字来叙述. #7. Let be the linear mapping that maps 2P into 2R defined by
10()(())(0)p x dx p x p σ⎛⎫ ⎪= ⎪⎝⎭
⎰ Find a matrix A such that
()x A ασαββ⎛⎫+= ⎪⎝⎭
. Solution
1(1)1σ⎛⎫= ⎪⎝⎭ 1/2()0x σ⎛⎫
= ⎪⎝⎭
11/211/2()101
0x ασαβαββ⎛⎫⎛⎫⎛⎫⎛⎫+=+= ⎪ ⎪ ⎪⎪⎝⎭⎝⎭⎝⎭⎝⎭
Hence, 11/210A ⎛⎫=
⎪⎝⎭ #10. Let σ be the transformation on 3P defined by
(())'()"()p x xp x p x σ=+
a) Find the matrix A representing σ with respect to 2[1,,]x x
b) Find the matrix B representing σ with respect to 2[1,,1]x x +
c) Find the matrix S such that 1B S AS -=
d) If 2012()(1)p x a a x a x =+++, calculate (())n p x σ.
Solution (a) (1)0σ=
()x x σ=
22()22x x σ=+
002010002A ⎛⎫ ⎪= ⎪ ⎪⎝⎭
(b) (1)0σ=
()x x σ=
22(1)2(1)x x σ+=+
000010002B ⎛⎫ ⎪= ⎪ ⎪⎝⎭
(c)
2[1,,1]x x +2[1,,]x x =101010001⎛⎫ ⎪ ⎪ ⎪⎝⎭
The transition matrix from 2[1,,]x x to 2[1,,1]x x + is
101010001S ⎛⎫ ⎪= ⎪ ⎪⎝⎭
, 1B S AS -=
(d) 2201212((1))2(1)n n a a x a x a x a x σ+++=++
#11. Let A and B be n n ⨯ matrices. Show that if A is similar to B then there exist n n ⨯ matrices S and T , with S nonsingular, such that
A ST =and
B TS =.
Proof There exists a nonsingular matrix P such that 1A P BP -=. Let 1S P -=, T BP =. Then
A ST =and
B TS =.
#12. Let σ be a linear transformation on the vector space V of dimension n . If there exist a vector v such that 1()v 0n σ-≠ and ()v 0n σ=, show that
(a) 1,(),,()v v v n σσ- are linearly independent.
(b) there exists a basis E for V such that the matrix representing σ with respect to the basis E is
000010000010⎛⎫ ⎪ ⎪ ⎪ ⎪⎝⎭
Proof
(a) Suppose that
1011()()v v v 0n n k k k σσ--++
+= Then 11011(()())v v v 0n n n k k k σσσ---+++=
That is, 12210110()()())()v v v v 0n n n n n k k k k σσσσ----++
+== Thus, 0k must be zero since 1()v 0n σ-≠.
211111(()())()v v v 0n n n n k k k σσσσ----++==
This will imply that 1k must be zero since 1()v 0n σ-≠.
By repeating the process above, we obtain that 011,,,n k k k - must be all zero.
This proves that
1,(),,()v v v n σσ- are linearly independent.
(b) Since 1,(),,()v v v n σσ- are n linearly independent, they form a basis for V .
Denote 112,(),,()εv εv εv n n σσ-===
12()εεσ=
23()εεσ=
…….
1()εεn n σ-=
()ε0n σ=
12[(),(),,()]εεεn σσσ121[,,,,]εεεεn n -=000010000010⎛⎫ ⎪ ⎪ ⎪ ⎪⎝⎭
#13. If A is a nonzero square matrix and k A O =for some positive integer k , show that A can not be similar to a diagonal matrix.
Proof Suppose that A is similar to a diagonal matrix 12diag(,,,)n λλλ. Then for each i , there exists a nonzero vector x i such that x x i i i A λ=
x x x 0k k i i i i i A λλ=== since k A O =.
This will imply that 0i λ= for 1,2,,i n =. Thus, matrix A is similar to the zero matrix. Therefore, A O =since a matrix that is similar to the zero matrix must be the zero matrix, which contradicts the assumption.
This contradiction shows that A can not be similar to a diagonal matrix. Or
If 112diag(,,,)n A P P λλλ-= then 112diag(,,,)k k k k n A P P λλλ-=.
k A O = implies that 0i λ= for 1,2,,i n =. Hence, B O =. This will imply that
A O =. Contradiction!。

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