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Name:- Dhanraj Vaghela
Branch:- Mechanical
Sem:- 02
Enrollment- 140990119060
From the desk of Dhanraj from SRICT
 Isomorphism:
other.eachtoisomorphicbetosaidare
andthen,tofrommisomorphisanexiststheresuch that
spacesvectorareandifMoreover,m.isomorphisancalledis
ontoandonetooneisthat:nnsformatiolinear traA
WVWV
WV
WVT 
 Thm 6.9: (Isomorphic spaces and dimension)
Pf:
.dimensionhaswhere,toisomorphicisthatAssume nVWV
onto.andonetooneisthat:L.T.aexistsThere WVT 
one-to-oneisT
nnTKerTT
TKer


0))(dim()ofdomaindim()ofrangedim(
0))(dim(
Two finite-dimensional vector space V and W are isomorphic if and only if
they are of the same dimension.
From the desk of Dhanraj from SRICT
.dimensionhavebothandthatAssume nWV
onto.isTnWT  )dim()ofrangedim(
nWV  )dim()dim(Thus
 
  .ofbasisabe,,,let
andV,ofbasisabe,,,Let
21
21
Wwww
vvv
n
n


nnvcvcvc
V
 2211
asdrepresentebecaninvectorarbitraryanThen
v
nnwcwcwcT
WVT


2211)(
follows.as:L.T.adefinecanyouand
v
It can be shown that this L.T. is both 1-1 and onto.
Thus V and W are isomorphic.
From the desk of Dhanraj from SRICT
vector.singleaofconsistsrangein theevery w
ofpreimagetheifone-to-onecalledis:functionA WVT 
 One-to-one:
.thatimplies
)()(inV,vanduallforiffone-to-oneis
vu
vu

 TTT
one-to-one not one-to-one
From the desk of Dhanraj from SRICT
Some important theorems related to one to one transformation
 Thm 1: A linear transformation T : V -> W is one to one if and only if ker(T)
={0}.
 Thm 2: A linear transformation T : V -> W is one to one if and only if
dim(ker(T)) = 0, i.e., nullity (T) = 0.
 Thm 3: A linear transformation T : V -> W is one to one if and only if
rank(T)=dim V.
 Thm 4: If A is an m x n matrix and TA : Rn -> Rn is multiplication by A then
TA is one to one if and only if rank (A)= n.
 Thm 5: If A is an n x n matrix and TA : Rn -> Rn is multiplication by A then
TA is one to one if and only if A is an invertible matrix.
From the desk of Dhanraj from SRICT
inpreimageahasin
elementeveryifontobetosaidis:functionA
V
WVT
w

 Onto:
(T is onto W when W is equal to the range of T.)
Thm 1: A linear transformation T : V -> W is onto if and only if rank (T)
= dim W
Thm 2: If A is an m x n matrix and TA : Rn -> Rm is multiplication by A
then TA is onto if and only if rank (A) = m.
 Let T : V -> W be a linear transformation and let dim V = dim W
(i) If T is one-to-one ,then it is onto.
(ii) If T is onto, then it is one-to-one.
From the desk of Dhanraj from SRICT
 Example :
neither.oronto,one,-to-oneiswhetherdetermineandof
rankandnullitytheFind,)(bygivenis:L.T.The
TT
ATRRT mn
xx 









100
110
021
)( Aa









00
10
21
)( Ab






110
021
)( Ac









000
110
021
)( Ad
Sol:
T:Rn→Rm dim(domain of T) rank(T) nullity(T) 1-1 onto
(a)T:R3→R3 3 3 0 Yes Yes
(b)T:R2→R3 2 2 0 Yes No
(c)T:R3→R2 3 2 1 No Yes
(d)T:R3→R3 3 2 1 No No
From the desk of Dhanraj from SRICT
 (Isomorphic vector spaces)
space-4)( 4
Ra
matrices14allofspace)( 14 Mb
matrices22allofspace)( 22 Mc
lessor3degreeofspolynomialallofspace)()( 3 xPd
)ofsubspace}(numberrealais),0,,,,{()( 5
4321 RxxxxxVe i
The following vector spaces are isomorphic to each other.
From the desk of Dhanraj from SRICT
Thank You
From the desk of Dhanraj from SRICT

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isomorphism

  • 1. Name:- Dhanraj Vaghela Branch:- Mechanical Sem:- 02 Enrollment- 140990119060 From the desk of Dhanraj from SRICT
  • 2.  Isomorphism: other.eachtoisomorphicbetosaidare andthen,tofrommisomorphisanexiststheresuch that spacesvectorareandifMoreover,m.isomorphisancalledis ontoandonetooneisthat:nnsformatiolinear traA WVWV WV WVT   Thm 6.9: (Isomorphic spaces and dimension) Pf: .dimensionhaswhere,toisomorphicisthatAssume nVWV onto.andonetooneisthat:L.T.aexistsThere WVT  one-to-oneisT nnTKerTT TKer   0))(dim()ofdomaindim()ofrangedim( 0))(dim( Two finite-dimensional vector space V and W are isomorphic if and only if they are of the same dimension. From the desk of Dhanraj from SRICT
  • 3. .dimensionhavebothandthatAssume nWV onto.isTnWT  )dim()ofrangedim( nWV  )dim()dim(Thus     .ofbasisabe,,,let andV,ofbasisabe,,,Let 21 21 Wwww vvv n n   nnvcvcvc V  2211 asdrepresentebecaninvectorarbitraryanThen v nnwcwcwcT WVT   2211)( follows.as:L.T.adefinecanyouand v It can be shown that this L.T. is both 1-1 and onto. Thus V and W are isomorphic. From the desk of Dhanraj from SRICT
  • 4. vector.singleaofconsistsrangein theevery w ofpreimagetheifone-to-onecalledis:functionA WVT   One-to-one: .thatimplies )()(inV,vanduallforiffone-to-oneis vu vu   TTT one-to-one not one-to-one From the desk of Dhanraj from SRICT
  • 5. Some important theorems related to one to one transformation  Thm 1: A linear transformation T : V -> W is one to one if and only if ker(T) ={0}.  Thm 2: A linear transformation T : V -> W is one to one if and only if dim(ker(T)) = 0, i.e., nullity (T) = 0.  Thm 3: A linear transformation T : V -> W is one to one if and only if rank(T)=dim V.  Thm 4: If A is an m x n matrix and TA : Rn -> Rn is multiplication by A then TA is one to one if and only if rank (A)= n.  Thm 5: If A is an n x n matrix and TA : Rn -> Rn is multiplication by A then TA is one to one if and only if A is an invertible matrix. From the desk of Dhanraj from SRICT
  • 6. inpreimageahasin elementeveryifontobetosaidis:functionA V WVT w   Onto: (T is onto W when W is equal to the range of T.) Thm 1: A linear transformation T : V -> W is onto if and only if rank (T) = dim W Thm 2: If A is an m x n matrix and TA : Rn -> Rm is multiplication by A then TA is onto if and only if rank (A) = m.  Let T : V -> W be a linear transformation and let dim V = dim W (i) If T is one-to-one ,then it is onto. (ii) If T is onto, then it is one-to-one. From the desk of Dhanraj from SRICT
  • 7.  Example : neither.oronto,one,-to-oneiswhetherdetermineandof rankandnullitytheFind,)(bygivenis:L.T.The TT ATRRT mn xx           100 110 021 )( Aa          00 10 21 )( Ab       110 021 )( Ac          000 110 021 )( Ad Sol: T:Rn→Rm dim(domain of T) rank(T) nullity(T) 1-1 onto (a)T:R3→R3 3 3 0 Yes Yes (b)T:R2→R3 2 2 0 Yes No (c)T:R3→R2 3 2 1 No Yes (d)T:R3→R3 3 2 1 No No From the desk of Dhanraj from SRICT
  • 8.  (Isomorphic vector spaces) space-4)( 4 Ra matrices14allofspace)( 14 Mb matrices22allofspace)( 22 Mc lessor3degreeofspolynomialallofspace)()( 3 xPd )ofsubspace}(numberrealais),0,,,,{()( 5 4321 RxxxxxVe i The following vector spaces are isomorphic to each other. From the desk of Dhanraj from SRICT
  • 9. Thank You From the desk of Dhanraj from SRICT