Digital Signal Processing
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; spectrum analysis using the DFT; parametric signal modeling and adaptive filtering. The course also covers applications of DSP in areas such as speech, audio and communication systems. The optional lab section (Section 02) provides a hands-on opportunity to explore the application of DSP theory to practical real-time applications in an embedded processing platform. See ee264.stanford.edu for more information. Register in Section 02 to take the lab. Undergraduate students taking the lab should register for 4 units to meet the EE design requirement. The optional lab section is not available to remote SCPD students.
Topics
- 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
- spectrum analysis using the DFT
- parametric signal modeling and adaptive filtering
Topics explicitly listed in official catalogue description
Sources
- Course catalogue ↗2026-2027