Digital Signal Processing

Course: ESE531

Catalog Level Description: This course covers the fundamentals of discrete-time signals and systems and digital filters. Specific topics include discrete-time Fourier transform (DTFT); Z-transforms; frequency response of linear discrete-time systems; sampling of continuous time signals, analog to digital conversion, sampling-rate conversion; basic discrete-time filter structures and types; finite impulse response (FIR) and infinite impulse response (IIR) filters; linear phase conditions; design of FIR and IIR filters; discrete Fourier transform (DFT) and the fast Fourier transform (FFT) algorithm. Applications in filtering and spectrum estimation, image filtering, adaptive filters, equalization.

• Learn the fundamentals of digital signal processing
• Provide an understanding of discrete-time signals and systems and digital filters
• Enable you to apply DSP concepts to a wide range of fields
• Gain the ability to read the technical literature on DSP
• Apply the techniques learned in a final project encompassing many different application types

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  Rough Syllabus (by weeks)

  1. Introduction
  2. Discrete-Time (DT) Signals
  3. Time-Domain Analysis of DT Systems
  4. Discrete Fourier Transform (DFT)
  5. Fast Fourier Transform (FFT)
  6. Discrete-Time Fourier Transform (DTFT)
  7. z-Transform
  8. Sampling of Continuous Time Signals
  9. Data Converters and Modulation
  10. Upsampling/Downsampling
  11. Discrete-Time Filter Design

  See Spring 2018 course calendar for day-by-day calendar with assignments.

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  Main Text

  • A. V. Oppenheim and R. W. Schafer (with J. R. Buck), Discrete-Time Signal Processing. 3rd. Edition, Prentice-Hall, 2010
  
  

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  Grading

  Grading is based on homework assignments, final project, midterm, and final exam.
  • Homework Assignments [20%]
  • Final Project [25%]
  • Midterm [25%]
  • Final [30%]

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  Policies

  Homework Turnin

  Homework will be due on select days indicated on the course calendar at midnight and must be uploaded into Canvas as a single PDF. Handwritten assignments will be accepted, but when specified computer generated figures, graphs and results must be submitted and everything should be still combined into a single PDF and submitted in Canvas. Homeworks must be legible and all work should be shown. Illegible submissions will not be graded.

  Late Assignments

  Late assignments will not be accepted or graded.

  If assignments or exams fall due on a religious holiday or for extenuating circumstances, please make arrangements with the instructor to accommodate before the posted due date.

  Absentees

  Use the Penn Course Absence Report (CAR) in Penn-in-Touch to report absences.

  Grade Adjustment

  Regrade requests must be submitted to the TA no later than 1 week after the assignment grades are released to the students. A cover sheet detailing the disrepency should be submitted with a copy of the original homework, and the TA reserves the right to regrade the entire assignment. Students are responsible for checking posted grades in a timely manner.

  Collaboration

  You may help each other understand how to use the CETS computers and course tools.

  Each student is expected to do his/her own work -- including developing the details, writing code, performing simulations, and writing the solutions. For the homeworks and projects, you are free to discuss basic strategies and approaches with your fellow classmates or others, but detail designs, implementations, analysis, and writeups should always be the work of the individual. If you get advice or insights from others that influenced your work in any way, please acknowledge this in your writeups.

  In general, you are expected to abide by Penn's Code of Academic Integrity. If there is any uncertainty, please ask.

  Previous Offerings

  • Spring 2017

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