MTH 420 - Sec 001
Models and Methods of Applied Mathematics

MW 2:00-2:50PM
STAG 210

F 2:00-2:50PM
MLC 109

Winter 2018


Dr. Nathan Louis Gibson  


Kidd 056

Office Hours:


Course Website:

Required Text:



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Course Description

Discrete and continuous mathematical models and methods for analysis, including linear analysis, equilibrium and minimum principles, calculus of variations, principal component analysis and orthogonal expansions, asymptotic and Fourier analysis, least squares, constrained and unconstrained optimization, inverse problems, and Monte Carlo techniques. Particular models and methods covered may vary annually.

Particular topics this year may include FFT, PCA, PCE, Lagrange Multipliers, Adjoints, Kalman Filter, Simplex, Duality, Kuhn-Tucker, and others.

Course design:
Thank you for your input to help design the course. I will incorporate many of the things you have already expressed, and maintain flexibility for us to take advantage of needs and opportunities as they arise. My goal is for you to be very actively involved in learning some topics in Appled Mathematics, in the context of learning various fundamental methods and how to use them in specific applications.

This will be a challenging course, and you should expect to spend a lot of time and effort on it; the ultimate responsibility for what you learn is your own. I hope you will find that mathematics is broad, rich, interesting, and useful, and that you can personally be mathematically creative and have a real feeling of accomplishment from it. We should also have fun and stretch our brains at the same time, which is what I think doing mathematics is all about.

I am designing the course to help you succeed in learning and have a productive experience, and to be well prepared for future study/occupation. Your work will have several components. A variety of types of work will allow you to shine in ways which best match your strengths. I expect that some people will excel with certain types of assignments, and others with different ones. Your course grade will be based on a combination of all these components.

You are expected to actively participate in class and keep up with producing quality written work, including advance preparation for class. The major categories are Homework, Lab, and Exam.

MTH 420 Measurable Student Learning Outcomes:TBD

MTH 520 Measurable Student Learning Outcomes:TBD

Accommodations for students with disabilities are determined and approved by Disability Access Services (DAS). If you, as a student, believe you are eligible for accommodations but have not obtained approval please contact DAS immediately at 541-737-4098 or at DAS notifies students and faculty members of approved academic accommodations and coordinates implementation of those accommodations. While not required, students and faculty members are encouraged to discuss details of the implementation of individual accommodations.

Students are expected to be familiar with Oregon State University's Statement of Expectations for Student Conduct.

Course Drop/Add Information: See Office of the Registrar and Academic Calendars

As preparation for this class, you should review the materials covered in MTH 256 and MTH 341.


Grade Distribution

Homework 60%
Computer Assignments 10%
Midterm Exam10%
Final Exam20%
Total 100%


Homework: This course has daily homework, including readings. Each day’s lesson has three equally important homework assignments associated to it:

A. Advanced preparation, where you read pages from the book and formulate questions related to this. These are submitted on-line.
B. Warm-up exercises, where you explore your basic understanding. Your initial work is submitted on-line before class; you also bring a copy to class, as this forms the basis for group work.
C. Graded exercises. These are submitted on-line before the class hour on the day due.

The first two of these are graded as Complete (Check +), Partially Complete (Check), Largely Incomplete (Check −) (Warm-up exercises are considered incomplete if you do not participate in class the day they are due.) The graded exercises will be more thoroughly graded.

You will be submitting the three parts of the homework on a rolling basis. Usually, part A will be due by the class meeting before the lesson (this allows me to discern where any difficulties lie); part B will be due on the day of the lesson (and the class meeting’s activities will be based on it); and part C will be due the next class meeting. You are encouraged to discuss homework problems with your classmates outside of class; however, you MUST write up and submit your own work.

Homework may sometimes, at my suggestion, be re-worked after I critique it, to bring it to perfection, due at the next class period after being returned by me. My goal is to help you perfect your work to your and my satisfaction.

Computational Lab

The will be a laboratory component to this course. We will meet in the MLC Computer Lab (Kidder Hall 109) on Fridays. We will be learning about Linux and Git (Professional Development) and Python (Programming), using the open sources resources available at There will be Lab assignments due weekly (with only a few programming problems in each). Collaboration is encouraged, but each student must submit his or her own code.


To be posted as we go.


There will be one 50 minute in-class midterm exam and a cummulative final exam. No notes nor books are allowed; however, you may use a basic scientific calculator and a 3 by 5 inch index card with handwritten notes on both sides (two for the final). No make-up midterm exams will given after the scheduled time under any circumstances. Scheduling conflicts with the final exam must be resolved in advance (see AR 16). Note that the times and dates of all final exams are set by the Registrar's Office and are available online as part of the General Catalog and Schedule of Classes.