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Lectures in abstract algebra II linear algebra

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Thông tin cơ bản

Tiêu đề Lectures in Abstract Algebra II. Linear Algebra
Tác giả Nathan Jacobson
Người hướng dẫn P. R. Halmos, Managing Editor, F. W. Gehring, C. C. Moore
Trường học Yale University
Chuyên ngành Mathematics
Thể loại textbook
Năm xuất bản 1953
Thành phố New Haven
Định dạng
Số trang 290
Dung lượng 7,43 MB

Cấu trúc

  • 1. Definition and examples (41)
  • 2. Compositions of linear transformations 33 3. The matrix of a linear transformation 36 4. Compositions of matrices (0)
  • 5. Change of basis. Equivalence and similarity of matrices. 41 6. Rank space and null space of a linear transformation 44 7. Systems of linear equations (51)
  • 8. Linear transformations in right vector spaces (59)
  • 9. Linear functions (61)
  • 10. Duality between a finite dimensional space and its conjugate space (63)
  • 11. Transpose of a linear transformation 56 12. Matrices of the transpose 58 13. Projections (0)
  • 4. Cyclic linear transformations (79)
  • 5. The cp[AJ-module determined by a linear transformation. 74 6. Finitely generated o-modules, 0, a principal ideal domain 76 7. Normalization of the generators of ~ and of ~ (0)
  • 8. Equivalence of matrices with elements in a principal ideal domain (0)
  • 9. Structure of finitely generated o-modules . 85 10. Invariance theorems (0)
  • 11. Decomposition of a vector space relative to a linear trans- (102)
  • 12. The characteristic and minimum polynomials 98 13. Direct proof of Theorem 13 (108)
  • 14. Formal properties of the trace and the characteristic poly- (113)
  • 15. The ring of o-endomorphisms of a cyclic o-module (116)
  • 16. Determination of the ring of o-endomorphisms of a finitely (118)
  • 17. The linear transformations which commute with a given lin- (120)
  • 18. The center of the ring ~ 113 (0)
  • CHAPTER IV: SETS OF LINEAR TRANSFORMATIONS 1. Invariant subspaces 115 2. Induced linear transformations 117 3. Composition series (11)
    • 4. Decomposability (132)
    • 5. Complete reducibility 124 6. Relation to the theory of operator groups and the theory of (0)
    • 7. Reducibility, decomposability, complete reducibility for a (138)
    • 8. The primary components of a space relative to a linear trans- formation (140)
    • 9. Sets of commutative linear transformations (143)
    • 3. Non-degenerate forms (150)
    • 4. Transpose of a linear transformation relative to a pair of bi- (152)
    • 5. Another relation between linear transformations and bilinear (155)
    • 6. Scalar products (157)
    • 7. Hermitian scalar products (160)
    • 8. Matrices of hermitian scalar products 152 9. Symmetric and hermitian scalar products over special divi- (0)
  • CHAPTER VI: EUCLIDEAN AND UNITARY SPACES 154 159 162 170 1. Cartesian bases (41)
    • 2. Linear transformations and scalar products (186)
    • 3. Orthogonal complete reducibility (187)
    • 4. Symmetric, skew and orthogonal linear transformations. 178 5. Canonical matrices for symmetric and skew linear transfor- (188)
    • 6. Commutative symmetric and skew linear transformations. 182 7. Normal and orthogonal linear transformations (192)
    • 8. Semi-definite transformations (0)
    • 9. Polar factorization of an arbitrary linear transformation 188 10. Unitary geometry (198)
    • 11. Analytic functions oflinear transformations (0)
  • CHAPTER VII: PRODUCTS OF VECTOR SPA9ES 1. Product groups of vector spaces (0)
    • 2. Direct products of linear transformations 202 3. Two-sided vector spaces (0)
    • 4. The Kronecker product (0)
    • 5. Kronecker products of linear transformations and of matrices 211 6. Tensor spaces (0)
    • 7. Symmetry classes of tensors (0)
    • 8. Extension of the field of a vector space (0)

Nội dung

Definition and examples

q,(X) ~ q,'(X) in the vector space ('A) -4 cf>'('A) is a linear transforma- tion in the vector space ffi of polynomials of degree ('A) -4 cf>('A + 1) - cf>('A) is a linear trans- formation in ['A]

This section explores the combinations of linear transformations, noting that the findings are also applicable to the broader context of o-homomorphisms of modules However, for clarity and simplicity, we will focus on the specific case that is most relevant to our discussion.

Suppose first that A and B are linear transformations of a vec- tor space ffi l into the same space ffi2 We define a mapping

A + B of ffi l into ffi2 by the equation

The equation (3) x(A + B) = xA + xB holds true for any x in ffil, demonstrating that the transformation A + B affects x by combining the images xA and xB Consequently, A + B serves as a single-valued transformation from ffil to ffi2.

= xA + xB + yA + yB = x(A + B) + y(A + B) and

(ax) (A + B) = (ax)A + (ax)B = a(xA) + a(xB)

A + B is a linear transformation of ffi1 into ffi2

The set of all linear transformations from ffi l to ffi2, denoted as ~(ffih ffi2), forms a commutative group when combined with the addition and composition operations We can confirm that both the associative and commutative laws are satisfied within this framework.

34 LINEAR TRANSFORMATIONS x[(A + B) + C] = x(A + B) + xC = xA + xB + xC, x[A + (B + C)] = xA + x(B + C) = xA + xB + xC, x(A + B) = xA + xB, x(B + A) = xB + xA

In the context of vector transformations, both (A + B) + C and A + (B + C) yield the same result for any x in m h, illustrating their equality Additionally, the commutative property is demonstrated as A + B equals B + A We introduce the zero mapping, denoted as 0, defined by the condition xO = 0, where 0 represents the zero vector in m 2 This mapping confirms that A + 0 = A and 0 + A = A for all A in ~(mh m 2), establishing 0 as the identity element for additive composition Furthermore, for any A in ~(mh m 2), we define -A as the mapping where x(-A) = -xA It is straightforward to verify that -A belongs to ~(mh m 2) and serves as the inverse of A, since x(A + (-A)) equals xA - xA = 0 for all x.

This completes the verification that ~(mh m 2 ), + is a commuta- tive group

We introduce next a second composition for linear transforma- tions This is defined for any A in ~(mh m 2 ) and any B in

~(m2' m3), and it is taken to be the resultant of A followed by B

As usual, we denote the resultant as AB Hence by definition x(AB) = (xd)B Consequently

(x + y)(AB) = ôx + y)A)B = (xA + yA)B = (xA)B + (yA)B

(ax)(AB) = ôax)A)B = (a(xdằB = aôxd)B) = a(x(ABằ

This shows that AB e ~(mh m3)'

As is well known, the product AB is an associative one, that is, if A e ~(mh m2), B e ~(m2' ma) and C e ~(ma, m4), then

(AB)C = A(BC); xôAB)C) = (x(ABằC = ôxd)B)C x(A(BCằ = (xd)(BC) = ôxA)B)C

We prove next the important distributive laws: If A d~(~h ~2)'

These follow from the following equations: x(A(B + C)) = (xA)(B + C) = (xA)B + (xA)C

= x(AB) + x(AC) = x(AB + AC) x((B + C)D) = (xB + xC)D = (xB)D + (xC)D

We now specialize the foregoing results to the case of the linear transformations in a single vector space~ It is clear that

In the mathematical structure defined as a ring, 2(~, ~) with the operation + forms a commutative group The set 2(~, ~) is closed under the operation, which is both associative and distributive concerning addition Additionally, the identity mapping x ~ x exists within this structure, denoted as 1, serving as the identity element in the ring 2, satisfying the condition Al = A = lA for all elements A.

Suppose next that

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