525.627.81 - Digital Signal Processing

Expanded Course Description

WHAT YOU REALLY NEED TO KNOW

I have taught this class a number of  times and have noticed a few things that I'd like to tell the students up-front.  For several years I taught this course with a co-instructor so you may find that I use a collective "we" instead of "I".

1. This is a graduate DSP class equivalent in content, effort, and value to that of a face-to-face (in class) version of an advanced class available at any top university. You will be learning the material in a distance learning environment. It will be helpful if you are comfortable in communicating via the Internet, downloading and posting  files, plus creating MS Word and PDF technical documents containing equations and figures. Some students find it helpful to have some capability to scan and paste printed pages into digital documents.

2. Students have a degree of convenience and flexibility afforded by the online environment and asynchronous nature where they can choose the time and schedule when to work on the class material. Although you have this flexibility, it is important that it be matched with a high level of commitment, planning and discipline to study the course modules regularly, and to be active in the discussions making meaningful contributions, completing and submitting weekly required homework assignments on time. All of these contribute to the leaning process, take time, and are a significant input to your final grade. Therefore, this course is not appropriate for students with limited time. It is generally better if this is the only graduate class that you take this semester and focus your efforts. Additionally, MATLAB is constantly upgraded by The MathWorks. Some of these changes are not always reflected in the instructions that are given on the course website. Students are expected to be persistent and patient in working through any problems with the assistants of the course instructor.

3. This class is fast paced. You are going to not only learn about Linear Time Invariant (LTI) systems, transform techniques, Finite Impulse Response (FIR), Infinite Impulse Response (IIR), filter structures, and applications, but also actually use them. Understanding derived from complex analysis will be reinforced and facilitated by software tools. You will start immediately building a library of real-world tools in the form of MATLAB m-file functions to process and analyze signals. 

4. This class is worth the effort. Although this class may take considerable effort, we have found that all students who, having paid the price to succeed, indicate that they learned an incredible amount and believe it was well worth the investment of their time.

Course Structure

The course materials are divided into modules which can be accessed by clicking Modules on the course menu. A module will have several sections including the overview, content, readings, discussions, and assignments. You are encouraged to preview all sections of the module before starting. Most modules run for a period of seven (7) days from Wednesday at 1AM to Tuesday 11:59PM when the Module Assignment is due.

Course Topics

See the Course Schedule section for a list of the topics covered.

Course Goals

• Explain digital signal processing (DSP) theoretical concepts including definitions, principles of operation, basis of analysis techniques and practical examples.
• Apply DSP theory and analysis skills to solve DSP problems, professionally documenting the approach, and analysis technique and when appropriate computer solutions.
• Formulate solutions to answer DSP questions including the evaluation of various approaches and techniques.
• Challenge DSP misconceptions or incomplete ideas in the understanding of DSP.
• Identify the relationship between mathematical techniques such as various signal transforms to permit multiple insightful views for a given problem or concept.

Course Learning Outcomes (CLOs)

• Develop an understanding of the fundamentals of digital signal processing and be able to analyze and design signal processing systems.
• Interpret results of different DSP systems and evaluate system performance based on their acquired knowledge.

Textbooks

Proakis, John G. and Manolakis, Dimitris G. (2007). Digital Signal Processing, Principles, Algorithms, and Applications. (4th Ed.). Pearson Prentice Hall.

ISBN 0-13-187374-1

Textbook information for this course is available online through the appropriate bookstore website: For online courses, search the MBS website.

Other Materials & Online Resources

Students should refer to Help & Support on the left menu for a listing of all the student services and support available to them.

Required Software

You will need access to a recent version of MATLAB. A license is provided at no cost to you, through JHU. Visit the JHU IT Services Portal. Log in with your JHED ID and type “Matlab” in the search bar. Click on “Matlab for Students” in the search results and follow the instructions provided.

Student Coursework Requirements

Participation:  10%
Assignments:  25%
Midterm Exam:  30%
Final Exam:  35%

Grading Policy

Grades are not curved and +'s and -'s are not assigned to grades.  Quibbling about a course grade at the end of the semester will not be tolerated.

"A"  = 100-90.0
"B" = 89.9 - 80.0
"C" = 79.9 - 70.0
"F" = 69.9 and Below

Course Policies

Students must request an extension to an deadline prior to the passing of the deadline.  No exceptions.

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.