CSE 135B Digital Signal Processing Design and Laboratory (2013-2014)

CSE 135B Digital Signal Processing Design and Laboratory

(Required for CSE. Selected Elective for CpE and EE.)
Catalog Data:

CSE 135B Digital Signal Processing Design and Laboratory (Credit Units: 3) Design and implementation of algorithms on a DSP processor and using computer simulation. Applications in signal and image processing, communications, radar, and more. Materials fee. Prerequisite: CSE135A/EECS152A. Computer Engineering, Electrical Engineering, and Computer Science Engineering majors have first consideration for enrollment. Same as EECS 152B. (Design units: 3)

Required Textbook:
. Edition, , 1969, ISBN-13 978-1439883037.

Recommended Textbook:
A. Lee Swindlehurst
Relationship to Student Outcomes
This course relates to Student Outcomes: CAC a, CAC c, CAC i, EAC a, EAC b, EAC c, EAC i, EAC k.
Course Learning Outcomes. Students will:

1. Characterize sampled systems in time and frequency domain. (CAC a, EAC a, EAC b)

2. Apply z-transform, DTFT, DFT and DWT to analyze and design DSP systems. (CAC a, CAC c, EAC a, EAC c)

3. Design basic FIR digital filters. (CAC a, CAC c, CAC i, EAC a, EAC b, EAC c, EAC i, EAC k)

4. Design basic IIR digital filters (using the bilinear transformation). (CAC a, CAC c, CAC i, EAC a, EAC b, EAC c, EAC i, EAC k)

5. Use DSP tools such as Matlab to analyze discrete systems and design digital filters. (CAC a, CAC i, EAC a, EAC b, EAC i, EAC k)

Prerequisites by Topic

Fourier and Z-transforms, linear system theory, C programming experience.

Lecture Topics:
  • MATLAB basics (week 1)
  • TMS320C6713 programming basics (weeks 1-3)
  • FIR filter design (weeks 3-4)
  • Spatial filter design (weeks 4-5)
  • IIR filter design (week 6)
  • Adaptive filter design (weeks 7-8)
  • Multi-rate signal processing (week 9)
  • Additional topics depending on class interest (speech coding, image processing, equalization, etc.) (week 10)
Class Schedule:

Meets for 1 hour of lecture and 6 hours of laboratory each week for 10 weeks.

Computer Usage:
  • Students are expected to have some experience programming in C/C++.
  • Experience with MATLAB is not necessary but helpful.
Laboratory Projects:

Using TMS320C6713: audio input/output, signal generation, FIR and IIR filter implementation, LMS adaptive echo cancellation. Using MATLAB: spectral analysis, FIR and IIR filter design, spatial filter design.

Professional Component

Contributes towards the Computer Science and Engineering major requirements for Engineering Topics courses and Major Design experience.

Design Content Description

This course is devoted to the application of digital signal processing techniques to the design of digital processors that implement various types of signal filtering, including static FIR and IIR filters and also dynamic adaptive filters. Students gain experience in how such digital processes are implemented in practice using a standard DSP platform (e.g., the Texas Instruments TMS320C6713 DSK) and also study more advanced design concepts using MATLAB. All homework assignments and lab projects require the students to apply design principles.

Lectures: 0%
Laboratory Portion: 100%
Grading Criteria:
  • Matlab Assignments: 33%
  • Hardware Labs: 33%
  • Final Exam: 34%
  • Total: 100%
Estimated ABET Category Content:

Mathematics and Basic Science: 0.0 credit units

Computing: 0.0 credit units

Engineering Topics: 3.0 credit units

Engineering Science: 0.0 credit units

Engineering Design: 3.0 credit units

October 1, 2014
Senate Approved:
April 29, 2013
Approved Effective:
2013 Fall Qtr