ECE 567:
Statistical Signal Processing
Fall 2021
ECE 567 WEB SITE CONTENTS:
MEETING TIME AND PLACE:

Day and time:

  • Tuesday and Thursday, 3:35 - 4:50 pm (1535 - 1650)

Location:

  • RE-258 (room 258 of the John T. Rettaliata Engineering Center)

COURSE STAFF:

  • Instructor:
    Dr. Geoffrey Williamson
    • Office: 128 Siegel Hall
    • Phone: 312-567-5960
    • E-mail: williamson [at] iit [dot] edu
    • Office Hours:
      Office Hours will be held online via Google Meet. My preference is to meet during the following times.
      • Tuesdays 11:00 am to 12:30 pm (1100 - 1230)
      • Thursdays 10:00 am to 12:00 pm (1000 - 1200)

      However, I am open to schedule at other times that are mutually acceptable. If there is need or demand, I will also arrange for group office hour sessions, either via Google Meet or via Blackboard Collaborate.

  • Grader:
    To be determined
    • Office:
    • Phone:
    • E-mail:
    • Office Hours: by appointment
TEXTBOOK:
  • Steven M. Kay, Fundamentals of Statistical Signal Processing, Vol. I Estimation Theory. Upper Saddle River, NJ: Prentice-Hall, Inc., 1993. ISBN-13: 978-0133457117. ISBN-10: 0133457117.

  • Other suggested references:
    • Steven M. Kay, Fundamentals of Statistical Signal Processing, Vol. II Detection Theory. Upper Saddle River, NJ: Prentice-Hall, Inc., 1998. ISBN: 0-13-504135-X
COURSE POLICIES:

Please be familiar with the following course policies.

  • COVID-19 Precautions and Face Coverings in Class.
    All students, faculty, staff, and campus visitors must wear face coverings indoors, regardless of vaccination status. This policy applies for class meetings on campus.

    Additionally, as a reminder, following other simple practices such as frequent and thorough hand washing, wiping down desks and seats with disinfectant wipes when possible, not sharing personal items such as pens and cell phones, and avoiding crowded hallways and other enclosed spaces will promote good health in and out of the classroom.

    Visit iit.edu/COVID-19 for details on Illinois Tech's response to coronavirus (COVID-19). For information from government authorities, please see the Centers for Disease Control and Prevention website at cdc.gov.

  • Disabilities.
    Reasonable accommodations will be made for students with documented disabilities. In order to receive accommodations, students must obtain a letter of accommodation from the Center for Disability Resources and make an appointment to speak with me as soon as possible. My office hours and contact information are listed above. The Center for Disability Resources is located in Suite 1C3-2 (on the first floor) at 3424 S. State Street, 312-567-5744 or disabilities@iit.edu.

  • Homework Policies.
    Please follow these rules when submitting homework papers. Any exceptions to these basic policies should be confirmed with the instructor before submitting your paper. Please also note that there are penalties on your homework score for failing to comply with these policies.
    • Please submit your assignments as pdf files via the Blackboard system. Be sure that your pdf is readable. Have each page in the pdf file be (approximately) 8 1/2 x 11 inches in size.
    • Your homework paper should present answers to the questions in the same order that they appear in the assignment. At the grader's discretion, zero credit may be given for work that appears out of order.
    • No late homeworks will be accepted without prior approval by the instructor. (Generally, approval of late homework submission requires there to be very extenuating circumstances. I drop the lowest homework score in part to accommodate the common situations that prevent persons from completing the assignments on time.)

  • Academic Honesty.
    It is your responsibility to be familiar with IIT's Code of Academic Honesty. (Consult the IIT Student Handbook for this code.)

    In particular, the work that you submit for homework and individual project assignments and your work on examination papers must be your own. You may consult with other students about homework and project assignments. In fact, discussion of the assignments is encouraged. However, the written material that is submitted must be your own. Such written material includes computer programs and the results of using computer programs (computed values, plots, etc.).

    If the above policy or any part of IIT's Code of Academic Honesty is violated in regard to a submitted homework assignment, a grade of zero will be assigned to the work AND your letter grade at the end of the course will be lowered (an A gets lowered to a B, a B gets lowered to a C, and a C gets lowered to a failing grade of E). If the above policy or any part of IIT's Code of Academic Honesty is violated in regard to a submitted project assignment or an examination paper, a punitive failing grade will be given in the course. In both cases, the matter will be reported to the appropriate university officials and offices. In the case of a second offense (with the first offense in this or any other course), I will pursue with the appropriate university officials your expulsion from the university.

    Violations of this policy include, but are not limited to: (a) copying another student's homework assignment, or any portion of it; (b) having your homework assignment or some portion of it be copied by another student (it is YOUR responsibility to be sure this doesn't happen; merely giving your homework assignment to another student when this allows them to copy it can lead to your violating the code of academic honesty); (c) including ideas from other sources (books, articles, web pages) in your submitted work without proper attribution (a common form of this is to copy the wording from a source verbatim without placing the passage in quotation marks and citing the source; however, merely restating the idea without attribution is also plagiarism - see the web piece Plagiarism, by Earl Babbie for examples); (d) using figures, drawings, diagrams, and pictures from other sources (including web sites!) without permission or attribution.

COURSE DOCUMENTS:

The following documents are available.

  • Course syllabus
  • List of course topics
  • Terminology for detection theory (a list of terms noted in the first two lectures)
  • Matlab m-files for generating plots used in Week #1's lectures
    • ROC_simple_example.m: Matlab m-file that plots the ROC curve for a constant signal in Gaussian noise
    • ENR_simple_example.m: Matlab m-file that plots the detection probability versus the energy-to-noise ratio, given different fixed false alarm probabilities, for a constant signal in Gaussian noise
  • Relationship between Q(x) and erfc (this document shows the relationship between the complementary cumulative distribution function and a function available in Matlab)
  • Matlab function files for implementing Q(x) and its inverse
    • Q.m: Matlab function file to calculate the value of Q(x)
    • Q_inv.m: Matlab function file to calculate from y the value of x such that y=Q(x) (i.e. x = Q-inv(y))
  • Matlab m-file used in lecture on the Cramer Rao Lower Bound (CRLB), example 3.5 from the text
  • Files used in lecture on Monte Carlo simulations of parameter estimates
  • Files used in lecture on iterative methods for computing ML estimates
    • example7p11.m: Matlab m-file that calculates iteration of Newton-Raphson and Scoring Method iterations from one initial condition.
    • example7p11v2.m: Matlab m-file that calculates iteration of Newton-Raphson and Scoring Method iterations from three initial conditions, using the same observation.
HOMEWORK ASSIGNMENTS:

Homework assignments, when available, will be posted at the course's Blackboard site. Assignments with due dates are simply listed here.

  • Homework Assignment #1 (due 9 September 2021)
  • Homework Assignment #2 (due 21 September 2021)
  • Homework Assignment #3 (due 30 September 2021)
  • Homework Assignment #4 (due 14 October 2021)
  • Homework Assignment #5 (due 26 October 2021)
  • Homework Assignment #6 (due 4 November 2021)
  • Homework Assignment #7 (due 11 November 2021)
  • Homework Assignment #8 (due 23 November 2021)
  • Homework Assignment #9 (due 2 December 2021)
HOMEWORK SOLUTIONS:

Solutions to the homework assignments, when available, will be posted at the course's Blackboard site.

EXAMINATIONS:

In-class examinations will be given on the following dates.

  • Midterm Examination #1: 7 October 2021
  • Midterm Examination #2: 16 November 2021
  • Final Examination: week of 6 December 2021, date/time to be determined
    • 120 minutes in length
    • Comprehensive

Here are examinations I have given in previous offerings of this course

The following file provides some of the answers to the Spring 2008 and Fall 2009 versions of Midtern Exam #1.

GRADING:

Homework: 15% (best 8 of 9 assignments)
Midterm Exam #1: 25%
Midterm Exam #2: 25%
Final Exam: 35%

The final is comprehensive.

COMPUTER SOFTWARE:

The homework assignments will require use of the Matlab software package. This software is available for use in all of IIT's computer labs, including those at the Rice Campus. Details about computer lab facilities may be found at https://ots.iit.edu/classrooms-labs.


This page last updated on 20 August 2021
Send comments and corrections to williamson [at] iit [dot] edu.