MATH 410 SUMMER 2004
(Prof. Bayly): SYLLABUS (tentative):
The timing may vary from this proposed timetable. Make sure to stay up to date with the course
as it actually evolves. The section
headings refer to sections in Olver and Shakiban; topics marked with an
asterisk* are not covered in O&S (yet!).
12 July: 1.1, 1.2, 1.3, 1.8. Review of vectors, matrices,
linear systems. Geometric interpretations. Gaussian elimination, echelon forms. Existence and general form of solutions of
linear systems.
13 July: 1.2, 1.3, 1.4, 1.5, 1.6. Vector and matrix
operations, transposes. Matrix optics
application*. LU factorization, matrix inversion. Row and column exchange issues. Rank and
nullity of matrix and transpose. Null vectors as “cycles”*.
14 July: 2.1, 2.3, 2.4, 2.5.
Vector spaces, subspaces, linear independence, basis and dimensions. Four
fundamental subspaces. General theory of
existence and/or uniqueness of solutions.
15 July: 2.6, 6.1, 6.2, 6.3.
Applications and special matrices.
Networks, circuits, bridges and trusses.
Review for exam 1.
16 July: Applications continued, currency arbitrage*. In-class review for exam 1.
19 July: 3.3. Norms, vector and matrix max norm. Invertibility
of near-identity and diagonally-dominant matrices, Jacobi iteration. EXAM 1 on material in chapters 1, 2, 6.
20 July: 3.1, 3.2, 3.4, 3.5. Inner products, length (2-norm).
Quadratic forms and symmetric matrices, Cholesky factorization,
positive-definite and other classifications. Maxima, minima, saddle
points. Gram matrices.
21 July: 4.1, 4.2. Minimization of multivariable quadratic
functions. Minimal length solutions of underdetermined linear systems*,
quadratic and linear formulations.
22 July: 4.3, 4.4, 4.5.
Least-squares approximate solution of overdetermined systems, normal
equations. Applications to data-fitting,
function approximation, and ranking of teams.
23 July: 3.2, 5.6. Angle between 2 vectors, orthogonal
vectors. Orthogonal complement of a set
of vectors. Orthogonality properties of
fundamental subspaces of a matrix. In-class
review for Exam 2.
26 July: 5.5. Projections parallel and perpendicular to
vectors. Least squares approximation as
projection onto column subspace. Projection matrices. EXAM 2 on material in chapters 3, 4.
27 July: 5.1, 5.2, 5.3. Orthogonal and orthonormal matrices,
Gram-Schmidt orthonormalization, QR factorization and algorithm. Areas, volumes, hypervolumes.
28 July: 1.9. Determinants and applications. Signed areas, volumes, and hypervolumes. NOTE:
we will completely skip chapter 7! This
chapter presents a more abstract view of the preceding 6 chapters, but as
O&S write on page ix of the preface, this material can be omitted if time
is an issue.
29 July: 8.1, 8.2, 8.3, 8.4, 8.5. Eigenvalues and
eigenvectors, and their properties. Characteristic
polynomial. Diagonal form of a matrix
(mention
30 July: 8.6. Singular Value Decomposition. In-class review for exam 3.
NOTE: Chapters 9 and
10 develop various aspects and applications of eigenvalue-eigenvector theory,
and the order in which you do them is not very important. I will do it in a different order than
O&S because I think it fits slightly better with UA’s Math410 but you
should not read much significance into either their or my choice of topic
order.
2 August: 10.3 Eigenvalues and norms, spectral radius,
Gershgorin Disk Theorem. EXAM 3 on material in chapters 5, 8.
3 August: 10.1, 10.2, 9.6. Powers and polynomials of matrix,
Cayley-Hamilton theorem, exponential of matrix.
4 August: 10.2, 10.4, 10.5. Linear discrete-time
systems. Fibonacci-like recursions,
Markov systems, network models. Long-time
behavior. Jacobi iteration (again),
Successive Over-Relaxation.
5 August: 9.1, 9.2, 9.3, 9.4. Linear continuous-time systems. Solution to 1st-order homogeneous
systems in terms of matrix exponentials, general method for matrix
exponential. Continuous-time Markov
systems.
6 August: 9.5. Mass-spring systems and higher-order
DEs. Vibrational modes, Rayleigh
quotients (again).
9 August: Course review.
10 August: Course review.
11 August: FINAL EXAM
half on chapters 9, 10 material, half comprehensive.