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| Lectures: |
MWF 11.00-11.50am, Herzstein Hall 212 |
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| Instructor: |
Mark Embree (embree@rice.edu),
Duncan Hall 3019, (713) 348-6160
Office hours: Tuesday 2-4pm (DCH 3092),
Friday 1pm-2pm (DCH 3019), or by appointment.
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Teaching
Assistants: |
Jesse Chan (jesse.chan@rice.edu),
Duncan Hall 3023, (713) 348-6113
Office hours: Wednesday 2-3pm (DCH 3023), or by appointment.
Charles Puelz (cpuelz@rice.edu),
Duncan Hall 2108
Office hours: Thursday 3-4pm (DCH 1044), or by appointment.
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| Recitations: |
Monday, 7:30-9:30pm, Duncan Hall 1070 (starting second week of class)
[Session on Sept. 2 = Labor Day is moved to Tuesday Sept. 3, same time, HZ 212.]
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| Physical Laboratory: |
This course is accompanied by an optional 1-credit laboratory in which students examine
concepts from the course more deeply through physical experiments. This experience provides
an excellent way to study the efficacy of mathematical models.
Learn more here.
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| Syllabus: |
pdf |
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| Prerequisites: |
CAAM 210 and MATH 212. Less formally: you should know multivariable calculus
and elementary matrix manipulations (matrix addition/multiplication,
Gaussian elimination), and have basic MATLAB fluency.
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| Objectives: |
CAAM 335 students learn to develop and analyze matrix-based mathematical models.
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| Outcomes: |
Upon completing this course, students should be able to:
1) develop matrix-based models of simple electrical and mechanical networks;
2) analyze the fundamental subspaces of a matrix;
3) solve systems of linear algebraic equations and least squares problems;
4) derive the spectral (eigenvalue) and singular value decompositions of a matrix;
5) apply the spectral decomposition to solve linear dynamical systems.
Students pursuing the four-credit (physical lab) option should also be able to:
6) assess the efficacy of a mathematical model compared to experimental data;
7) solve basic linear inverse problems with both simulated and real data.
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| Grade Policy: |
60% exams, 40% problem sets
Class participation will influence borderline and potential A+ grades.
Improving performance over the course of the semester will also be considered.
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| Absence Policy: |
Students are strongly encouraged to contribute to our class community
by attending and participating in lectures and active learning activities.
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| Text: |
Steven J. Cox, Matrix Analysis in Situ.
PDF file available here.
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| Exams: |
Three take-home, three-hour, closed-book exams will each
account for 20% of the final grade.
Each of these pledged exams must be your individual, unassisted effort.
Consult the calendar for approximate exam dates.
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| Problem Sets: |
Problem sets will be assigned roughly once a week, due at 5pm on the specified date.
Mathematically rigorous solutions are expected; strive for clarity and elegance.
You may collaborate on the problems, but your write-up must be your own independent work.
Transcribed solutions and copied MATLAB code are both unacceptable.
You may not consult solutions from previous sections of this class.
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| Late Policy: |
You may turn in two problem sets at 5pm on the next class day without penalty.
Subsequent late assignments will be penalized 20% each. Homework will not be
accepted more than one class period late. (You may not use
two `lates' on one assignment.) In exceptional circumstances, contact the
instructor as soon as possible: we adhere to Student Health's
`No Note' policy.
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| Re-Grade Policy: |
If your work has been graded incorrectly, you may submit a re-grade request.
Clearly explain the perceived error on a separate sheet of paper, staple it to the front
of your graded paper, and give it to the instructor.
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| MATLAB: |
Most homework assignments will require a modest amount of MATLAB programming.
Your solutions should adhere to good programming standards, and must not be copied
from another student. Consult the course web site for pointers to MATLAB resources.
You might also consult:
D. J. Higham and N. J. Higham, MATLAB Guide, 2nd ed.
Getting Started with MATLAB from MathWorks
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