525.631.81 - Adaptive Signal Processing

Course Structure

The course materials are divided into modules which can be accessed by clicking Course Modules on the left menu. A module willhave several sections including the lectures, readings, discussions, and assignments. You are encouraged to complete the reading assignment prior to starting the lectures. Most modules run for a period of seven (7) days, exceptions are noted on the Course Outline page. You should regularly check the Calendar and Announcements for assignment due dates.

Course Goals

1. Acquire a “toolbox” of adaptive filtering techniques and understand the conditions in which they are most effective.
2. Provide the ability to determine the optimal filter and theoretical performance of adaptive filtering techniques in known environments. 
3. Provide the ability to understand and apply these techniques to simulated signals in an unknown environment in order to gain improvements performance.

Course Learning Outcomes (CLOs)

• Calculate the optimal linear filter that minimizes the Mean Squared Error (MSE) between the estimated signal (filter output) and the desired signal in wide sense stationary scenarios.
• Design adaptive algorithms that enable an iterative estimation and tracking of the optimal solution in time-varying scenarios.
• Design adaptive structures and apply to various problem domains such as adaptive equalization, interference cancellation, linear prediction, and beam forming.
• Apply adaptive filtering techniques to simulated signals in an unknown environment in order to recover the corrupted signal-of-interest.

Textbooks

Adaptive Filter Theory, 5th Edition, Simon Haykin, 2014, Pearson, ISBN-13: 9780132671453

Textbook information for this course is available online through the appropriate bookstore website: For online courses, search the MBS website at http://ep.jhu.edu/bookstore.

Required Software

MATLAB

You will need access to a recent version of MATLAB with the Signal Processing Toolkit. The MATLAB Total Academic Headcount (TAH) license is now in effect. This license is provided at no cost to you. Send an email to software@jhu.edu to request your licensefile/code. Please indicate that you need a standalone file/code. You will need to provide your first and last name, as well as your Hopkins email address. You will receive an email from Mathworks with instructions to create a Mathworks account. The MATLAB software will be available for download from the Mathworks site.

Student Coursework Requirements

It is expected that each module will take approximately 7–10 hours per week to complete. Here is an approximate breakdown: reading the assigned sections of the texts (approximately 3–4 hours per week) as well as some outside reading, listening to the audio annotated slide presentations (approximately 2–3 hours per week), and homework and MATLAB assignments(approximately 2–3 hours per week).

This course will consist of the following basic student requirements:

Preparation and Participation (Module Discussions) (10% of Final Grade Calculation)

You are responsible for carefully reading all assigned material and being prepared for discussion. The majority of readings are from the course text. Additional reading may be assigned to supplement text readings.

Post your initial response to the discussion questions by the evening of day 3 for that module week. Posting a response to the discussion question is part one of your grade for module discussions (i.e., Timeliness).

Part two of your grade for module discussion is your interaction (i.e., responding to classmate postings with thoughtful responses and Critical Thinking). Just posting your response to a discussion question is not sufficient; we want you to interact with your classmates. Be detailed in your postings and in your responses to your classmates' postings. Feel free to agree or disagree with your classmates. Please ensure that your postings are civil and constructive.

I will monitor module discussions and will respond to some of the discussions as discussions are posted. In some instances, I will summarize the overall discussions and post the summary for the module.

Evaluation of preparation and participation is based on contribution to discussions.

Preparation and participation is evaluated by the following grading elements:

1. Timeliness (50%)
2. Critical Thinking (50%)

Preparation and participation is graded as follows:

100–90 = A—Timeliness [regularly participates; all required postings; early in discussion; throughout the discussion]; Critical Thinking [rich in content; full of thoughts, insight, and analysis].

89–80 = B—Timeliness [frequently participates; all required postings; some not in time for others to read and respond];Critical Thinking [substantial information; thought, insight, and analysis has taken place].

79–70 = C—Timeliness [infrequently participates; all required postings; most at the last minute without allowing forresponse time]; Critical Thinking [generally competent; information is thin and commonplace].

Assignments (10% of Final Grade Calculation)

Weekly homework includes technical problems from the text book as well as MATLAB computer assignments. Technicalproblems provide opportunities to demonstrate the theoretical and mathematical aspects of each topic. MATLAB computer assignments measure the ability to apply the theory in practical scenarios to improve the estimation performance.

All assignments are due according to the dates in the Calendar.

Late submissions will be reduced by one letter grade for each week late (no exceptions without prior coordination with the instructors).

Quantitative assignments are evaluated by the following grading elements:

1. Each part of question is answered (20%)
2. Assumptions are clearly stated (20%)
3. Intermediate derivations and calculations are provided (25%)
4. Answer is technically correct and is clearly indicated (25%)
5. Answer precision and units are appropriate (10%)

100–90 = A—All parts of question are addressed; All assumptions are clearly stated; All intermediate derivations and calculations are provided; Answer is technically correct and is clearly indicated; Answer precision and units are appropriate.

89–80 = B—All parts of question are addressed; All assumptions are clearly stated; Some intermediate derivations andcalculations are provided; Answer is technically correct and is indicated; Answer precision and units are appropriate.

79–70=C—Most parts of question are addressed; Assumptions are partially stated; Few intermediate derivations andcalculations are provided; Answer is not technically correct but is indicated; Answer precision and units are indicated but inappropriate.

<70=F—Some parts of the question are addressed; Assumptions are not stated; Intermediate derivations and calculations are not provided; The answer is incorrect or missing; The answer precision and units are inappropriate or missing.

Course Project (30% of Final Grade Calculation)

The course project will be assigned midway through the course. Students are given a signal corrupted by an unknown environment and must apply multiple adaptive filtering techniques to try and recover the corrupted signal-of-interest(SOI). Project includes MATLAB algorithm development and performance testing, as well as a final report that describes the problem, proposed solution, theoretical background, simulation results, summary and lessons learned.

The course project is evaluated by the following grading elements:

1. Technical Approach and Theoretical Analysis: Ability to describe the problem, and present a well thought outapproach to the solution backed by the theory presented in the course. (30%)
2. Simulation Results: Perform a minimum of 3 adaptive techniques, capture the performance results.(40%)
3. Conclusions and Lessons Learned: Presentation of analysis or simulation results and summary of strengths and weakness of each technique. Describe what you learned from the process of applying the techniques in the class to this project. What will you and won’t you do next time? (20%)
4. Innovation: Qualitative assessment of how you creatively applied the techniques of the class to the project.The practical application of adaptive filtering techniques allows great flexibility in the engineering decisions used including filter structure, adaptation algorithms, system parameters, and the overall solution. How did youcreatively combine or extend the techniques presented in the book? (10%)

Course Project is graded as follows:

100–90 = A—Student demonstrated excellent understanding of the problem space and theoretical background of solution. Simulations included 3 adaptive techniques with a thoughtful analysis of the results including detailed comparisons of the strengths and weakness of each technique. Innovative approach that used creative combinations or extensions of the techniques applied in class.

89–80 = B— Student demonstrated very good understanding of the problem space and theoretical background of solution. Simulations included 3 adaptive techniques with a thoughtful analysis of the results including detailed comparisons of the strengths and weakness of each technique. Solution demonstrated some creativity in the application, but primarily focused on a solid implementation of the techniques as presented in the book.

79–70 = C— Student demonstrated basic understanding of the problem space and theoretical background of solution.Simulations included 3 adaptive techniques with basic analysis of the results including some comparisons of the strengths and weakness of each technique. Solution demonstrated very little creativity beyond the basic implementationof the techniques in the book.

Exams (50% of Final Grade Calculation: 25% for Midterm and 25% for Final)

The midterm exam will be available in Module 7 and the final exam will be available in the next-to- last Module. You will have one week to complete the exams and they will be due by 5PM exactly one week from their release. You may use the course text to complete the exams. To receive partial credit, you must show your work.

Grading Policy

Assignments are due according to the dates posted in your Canvas course site. You may check these due dates in the Course Calendar or the Assignments in the corresponding modules. I will post grades one week after assignment due dates.

We generally do not directly grade spelling and grammar. However, egregious violations of the rules of the English language will be noted without comment. Consistently poor performance in either spelling or grammar is taken as an indication of poor written communication ability that may detract from your grade.

A grade of A indicates achievement of consistent excellence and distinction throughout the course—that is, conspicuous excellence in all aspects of assignments and discussion in every week.

A grade of B indicates work that meets all course requirements on a level appropriate for graduate academic work. These criteriaapply to both undergraduates and graduate students taking the course.

Final grades will be determined by the following weighting:

Academic Policies

Deadlines for Adding, Dropping and Withdrawing from Courses

Students may add a course up to one week after the start of the term for that particular course. Students may drop courses according to the drop deadlines outlined in the EP academic calendar (https://ep.jhu.edu/student-services/academic-calendar/). Between the 6th week of the class and prior to the final withdrawal deadline, a student may withdraw from a course with a W on their academic record. A record of the course will remain on the academic record with a W appearing in the grade column to indicate that the student registered and withdrew from the course.

Academic Misconduct Policy

All students are required to read, know, and comply with the Johns Hopkins University Krieger School of Arts and Sciences (KSAS) / Whiting School of Engineering (WSE) Procedures for Handling Allegations of Misconduct by Full-Time and Part-Time Graduate Students.

This policy prohibits academic misconduct, including but not limited to the following: cheating or facilitating cheating; plagiarism; reuse of assignments; unauthorized collaboration; alteration of graded assignments; and unfair competition. Course materials (old assignments, texts, or examinations, etc.) should not be shared unless authorized by the course instructor. Any questions related to this policy should be directed to EP’s academic integrity officer at ep-academic-integrity@jhu.edu.

Students with Disabilities - Accommodations and Accessibility

Johns Hopkins University values diversity and inclusion. We are committed to providing welcoming, equitable, and accessible educational experiences for all students. Students with disabilities (including those with psychological conditions, medical conditions and temporary disabilities) can request accommodations for this course by providing an Accommodation Letter issued by Student Disability Services (SDS). Please request accommodations for this course as early as possible to provide time for effective communication and arrangements.

For further information or to start the process of requesting accommodations, please contact Student Disability Services at Engineering for Professionals, ep-disability-svcs@jhu.edu.

Student Conduct Code

The fundamental purpose of the JHU regulation of student conduct is to promote and to protect the health, safety, welfare, property, and rights of all members of the University community as well as to promote the orderly operation of the University and to safeguard its property and facilities. As members of the University community, students accept certain responsibilities which support the educational mission and create an environment in which all students are afforded the same opportunity to succeed academically. 

For a full description of the code please visit the following website: https://studentaffairs.jhu.edu/policies-guidelines/student-code/

Classroom Climate

JHU is committed to creating a classroom environment that values the diversity of experiences and perspectives that all students bring. Everyone has the right to be treated with dignity and respect. Fostering an inclusive climate is important. Research and experience show that students who interact with peers who are different from themselves learn new things and experience tangible educational outcomes. At no time in this learning process should someone be singled out or treated unequally on the basis of any seen or unseen part of their identity. 
 
If you have concerns in this course about harassment, discrimination, or any unequal treatment, or if you seek accommodations or resources, please reach out to the course instructor directly. Reporting will never impact your course grade. You may also share concerns with your program chair, the Assistant Dean for Diversity and Inclusion, or the Office of Institutional Equity. In handling reports, people will protect your privacy as much as possible, but faculty and staff are required to officially report information for some cases (e.g. sexual harassment).

Course Auditing

When a student enrolls in an EP course with “audit” status, the student must reach an understanding with the instructor as to what is required to earn the “audit.” If the student does not meet those expectations, the instructor must notify the EP Registration Team [EP-Registration@exchange.johnshopkins.edu] in order for the student to be retroactively dropped or withdrawn from the course (depending on when the "audit" was requested and in accordance with EP registration deadlines). All lecture content will remain accessible to auditing students, but access to all other course material is left to the discretion of the instructor.