ECGR6114 Digital Signal Processing II Fall 2017
Prof. Weldon: EPIC Building Room 2228, email@example.com
Course Web site: see courses link on http://coefs.uncc.edu/tpweldon/
Office hours: see my home page http://coefs.uncc.edu/tpweldon/
Textbooks: Statistical Digital Signal Processing and Modeling,
Monson Hayes, John Wiley, 1996.
Text2: TBD (handouts for now)
Optional: Discrete-Time Signal Processing:, Oppenheim and
Schaffer, Prentice Hall, 2nd ed., 1998.
DO NOT order hardware until told to do so (in case of any changes).
If the class is small, some hardware is likely to be provided.
Required Hardware: NXP FRDM-K64F plus materials/cables/etc.
Required Software: mbed.org developer account to program the FRDM-K64F
Alternative: See note on alternative hardware/software projects, in
addition, instructor is likely to have alternative projects.
For introduction to K64F, see prior year final projects and "blinky"
All students enrolling must be sufficiently familiar with Java or C++
or learn such skills outside class to complete the final project. If you
have some special final project that your advisor wishes to substitute
and supervise, or that you wish to propose, instructor must approve it
in writing. Such alternative projects are typically at a level that
they would be submitted and published at an IEEE conference.
Exams may be open book, NO calculators. Plan is to allow hardcopy (NO
papers/copies/ebooks) of one or both of the above books during exams/quiz.
Quizzes may or may not be announced. Grading: 60% projects/quizzes/etc.,
with an end-of-semester IEEE-format paper/project weighted approx.
in proportion to time, and 40% exam. NOTE: instructor may change weights.
Scale: 90-100 A, 80-89 B, 70-79 C, 60-69 D, with "curve,"
if any, entirely at the discretion of the instructor. See prior year
projects, exams, handouts, quizzes on website.
This will be a hands-on, interactive, learn-by-doing course, hence
attendance is mandatory, and unexcused absences result in low grades.
Grading will be based on quizzes, projects, reports, attendance,
assignments, and so forth as the course progresses. Groups will be
formed, but every student must be prepared to demonstrate every
assignment on their own. NOTE: during any demos, the instructor
may select and question any member of a group for the demo. Expect a
low grade for poor attendance/participation, since the in-class work
is a large (~50%) component of the course.
Collaboration (not copying) on homework and computer projects is encouraged.
However, different project groups may NOT share program code or report
material. All computer projects and DSP code MUST be done in Mathcad, or
other assigned languages (some projects may use java/C++/NetBeans/mbed).
Class attendance and participation are expected, repeated absence may
result in grade reduction or failure.
***NOTE: You MUST do programming using Mathcad, or assigned languages.***
The course will roughly follow the outline below; key topics are noted.
1 Review of DSP fundamentals, Sampling, Aliasing, Quantization
z-transform, DTFT, DFT, Matrix Forms
2 Classical filters impulse invar., bilinear Transform, windows
3 Signal Modelling and Pade filter design
4 Least squares and Prony filter design methods
5 All-pole Prony, autocorrelation and covariance Methods
6 Digital impedance models and state variable models
7 Random processes, ARMA models, Yule-Walker
8 Spectral Estimation
11 Wiener Filters
12 Recursive least squares
13-14 Final project
15 Final project report and demo
Final Exam See Video Presentation and Review below
Video Presentation and Peer Reviews: Topic TBD (final project).
Every group must upload a 5 minute anonymous video clip of a
presentation on/before 5 PM of the night before the scheduled final
exam, so that all videos will be ready online for peer review during
the scheduled final exam meeting time. In addition, a pdf of the
presentation slides must be emailed to the instructor by the same
deadline (as a backup in case of video technical difficulties).
As an online final examination class session, each individual student
must view randomly assigned videos during the final exam period,
and/or take an online quiz at instructor discretion. The video and
reviews will be worth approximately one quiz. (TBD).
Excused absence makeups: May be during scheduled last class period.
Makeups will usually cover cumulative course material.
If you miss an exam/quiz for any reason, you will receive a grade of zero
(exceptional circumstances must be documented and/or approved by the
instructor at least 24 hours prior to the exam). Any special exam or project
accommodation request should be made no later than the class meeting one week
before the exam or project. Frequent absence from class or labs may result
in a severe grade reduction. Late projects will not be accepted, and/or may
be penalized up to 30 percent per day, solely at the instructor's discretion.
Absence from each project session, or early departure before attendance is
taken, will result in 30% grade reduction per absence, beyond 2 absences.
The instructor is free to assign students to any project group at any time.
Appeals regarding final grade must be communicated to instructor within
14 days after end of semester, since any residual materials may be destroyed
thereafter. Departure from the classroom during any quiz or exam will
result in a grade of zero. Students are responsible for submitting all
forms to Disability Services, and must provide a letter of accommodation
from Disability Services in the first week or two of the semester (see
their office for more information). Use of computers during class
will result in 20% deduction on next assignment and/or expulsion. Audio
or video recordings are not permitted, and all course content are
copyright by Thomas P. Weldon. NOTE: Final grading may include a subjective
component, at instructor discretion, based on the above rough weightings
PLUS the instructor's overall evaluation of student performance in project
sessions and class participation.
It is the responsibility of the student to be familiar with the academic
regulations, degree requirements, religious accommodation for students,
course requirements, and all other requirements, policies, and procedures
set forth in the current University Catalog and all University Policies.
The official university guidelines supersede any contradictions that may
exist in this handout. Violations may result in reduction of grades,
zero grade, fines, suspension, course failure, or other adverse consequences.
In addition, a proper classroom environment is expected by all students,
and therefore any disorderly or disruptive conduct or other negative impacts
on the classroom, solely at the instructor's discretion, will result in
expulsion from such class with a grade of zero for corresponding material,
and/or other adverse sanctions as may be deemed appropriate. Use of
computers, tablets, phones, etc. during class are disruptive to class.
If there are any issues or problems within a group, students must
follow the Project Problem Resolution Guidelines provided on the
The course policies set forth in this syllabus may be modified at any time
by the course instructor. Notice of such changes may be by announcement in
class and/or by email to the student's UNCC email address.
ALL STUDENTS MUST MEET PREREQUISITES AND COREQUISITES FOR THIS COURSE as
published in the UNCC Catalog.
Prerequisite: Permission of department. In general, students are expected
to have had a first course in DSP including z-transform, etc..
GRADUATE LEVEL SECTIONS
Higher-level graduate sections are required to do a final project of
commensurate challenge, as determined by the instructor's approval.