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. Prerequisites: EE 102A and EE 102B or equivalent, basic programming skills (Matlab and C++)