Digital Signal Processing

EE264

Stanford School of Engineering


Thumbnail

Description

Advances in integrated circuit technology have had a major impact on where and how digital signal processing techniques and hardware are applied. An understanding of digital signal processing fundamentals and techniques is essential for anyone whose work is concerned with signal processing applications.

This course introduces the basic concepts and principles underlying discrete-time signal processing. Concepts will be illustrated using examples of standard technologies and algorithms.

Students who take the 4-unit version of the course will be expected to complete an additional 4-week project and report.

Instructor(s)

Prerequisites

EE102A and EE102B or equivalent. Students should also have basic programming skills in Matlab and C++.

Topics include

  • Sampling and multi-rate systems
  • Oversampling and quantization in A-to-D conversion
  • Properties of LTI systems
  • Digital filter design
  • Discrete Fourier Transform and FFT
  • Parametric signal modeling
  • Applications in speech/audio processing, autonomous vehicles and software radio

Note on Course Availability

The course schedule is displayed for planning purposes – courses can be modified, changed, or cancelled. Course availability will be considered finalized on the first day of open enrollment. For quarterly enrollment dates, please refer to our graduate certificate homepage.