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Math 115AH: General Course Outline

Catalog Description

115A. Linear Algebra. (5) Lecture, three hours; discussion, two hours. Requisite: course 33A with grade of B or better. Techniques of proof, abstract vector spaces, linear transformations, and matrices; determinants; inner product spaces; eigenvector theory. Honors course parallel to course 115A. P/NP or letter grading.

Math 115A is a core mathematics course required of all the various mathematics majors. The course material can be regarded as an elaboration of the linear algebra already covered in Math 33A. However, the level of abstraction and the emphasis on proof technique make this a difficult course for many students. Successful students emerge from the experience not only with a better understanding of linear algebra, but also with a higher level of mathematical maturity, better equipped to deal with abstract concepts.

The material covered in Math 115A includes linear independence, bases, orthogonality, the Gram-Schmidt process, linear transformations, eigenvalues and eigenvectors, and diagonalization of matrices. These topics are all covered in Math 33A though only in the context of Euclidean space. Topics in Math 115A that go beyond Math 33A include inner product spaces, adjoint transformations, and the spectral decomposition theorem for self-adjoint operators.

Three or four sections of Math 115A are offered each term. Also, an honors version Math 115AH runs parallel to Math 115A in some quarters. The content of Math 115AH is as follows:
Vector spaces, subspaces, basis and dimension, linear transformations and matrices, rank and nullity, change of basis and similarity of matrices, inner product spaces, orthogonality and, orthonormality, Gram-Schmidt process, adjoints of linear transformations and dual spaces, quadratic forms and symmetric matrices, orthogonal and unitary matrices, diagonalization of hermitian and symmetric matrices, eigenvectors and eigenvalues, and their computation, exponentiation of matrices and application to differential equations, least squares problems, trace, determinant, canonical forms. Systems of linear equations: solvability criteria, Gaussian elimination, row-reduced form, LU decomposition.

Textbook

S. Friedberg, et al, Linear Algebra, Custom UCLA 4th Ed., Prentice Hall.
Book is Subject to Change Without Notice

Outline Updated: June 2005

Schedule of Lectures

Lecture Section Topics

1

1.2

Vector Spaces over a Field

2

1.3

Subspaces

3

1.4, 1.5

Linear Combinations and Systems of Linear Equations; Linear Dependence and Linear Independence

4

1.5, 1.6

Linear Dependence and Linear Independence; Bases and Dimensions

5

1.6

Bases and Dimensions

6

1.6

Bases and Dimensions

7

2.1

Linear Transformations, Null Spaces, and Ranges

8

2.1

Linear Transformations, Null Spaces, and Ranges

9

2.1, 2.2

Linear Transformations, Null Spaces, and Ranges; The Matrix Representation of a Linear Transformation

10

.

Midterm #1

11

2.2

The Matrix Representation of a Linear Transformation

12

2.3

Composition of Linear Transformations and Matrix Multiplication

13

2.4

Invertibility and Isomorphisms

14

2.4, 2.5

Invertibility and Isomorphisms; The Change of Coordinate Matrix

15

2.5

The Change of Coordinate Matrix

16

4.4

Summary - Important Facts about Determinants

17

5.1

Eigenvalues and Eigenvectors

18

5.1

Eigenvalues and Eigenvectors

19

5.2

Diagonalizability

20

5.2

Diagonalizability

21

5.2

Diagonalizability

22

.

Midterm #2

23

6.1

Inner Products and Norms

24

6.1, 6.2

Inner Products and Norms; The Gram-Schmidt Orthogonalization Process and Orthogonal Complements

25

6.2

The Gram-Schmidt Orthogonalization Process and Orthogonal Complements

26

6.3

The Adjoint of a Linear Operator

27

6.4

Normal and Self-Adjoint Operators

28

6.4

Normal and Self-Adjoint Operators

29

.

Catch-up, Review