Digital Signal Processing

Course Description

Digital signal processing (DSP) techniques and design of DSP applications. Topics include: discrete-time random signals; sampling and multi-rate systems; oversampling and quantization in A-to-D conversion; properties of LTI systems; quantization in fixed-point implementations of filters; digital filter design; discrete Fourier Transform and FFT; and spectrum analysis using the DFT. In the design part of the course, students develop basic DSP applications on an embedded processing platform. The 4-unit version of the course, which meets the EE design requirement, adds a final 4-week project and report. See ee264.stanford.edu for more information. 

Course Details

  • Grading Basis: Letter Grade or Credit/No Credit
  • Unit-Range Information: Optional one-unit project and report.

Prerequisites

EE 102A and EE 102B or equivalent; basic programming skills (MATLAB and C++)

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