EE264 Digital Signal Processing Hands-On Lab Option for Winter Quarter! Instructors: Ron Schafer and Fernando Mujica Digital Signal Processing (DSP) is at the heart of almost all modern technology. Applications of signal processing include some of the hottest current technology trends: internet of things (IoT), cloud computing, software-defined radios, robotics, autonomous vehicles, etc. In EE264 (3 credit hours), you will learn the fundamentals of DSP: • Discrete-time (D-T) random signals • Sampling, reconstruction, D-T filtering, multi-rate systems • Quantization in analog to digital conversion, and oversampling • Properties of linear time invariant (LTI) systems • Quantization effects in fixed-point implementations of filters • Digital filter design • Discrete Fourier Transform (DFT) and FFT • Spectrum analysis using the DFT • Parametric signal modeling UPDATED EE264 lab option (4 credit hours) This hands-on component will focus on practical implementations of DSP applications on embedded processors. You will have access to an embedded processor board (DSP Shield 1 ) and accessories. The course will be comprised of a few predefined labs to get familiar with the hardware and experiment with the theory discussed in class. For the final project, we will implement an audio-band orthogonal frequency division multiplexing (OFDM) receiver or you can propose your own project (subject to instructor approval). Some possible projects include: - Acoustic noise suppression - Programmable audio equalizer - Tree-structured subband coding of audio (MP3) - Phase vocoder (aka, a pitch shifter) - Time/frequency analyzer (spectrogram) - Digital FM/AM communications - OFDM communication link in the audio band - Speech preprocessing for machine learning recognizer The labs and projects are designed so that they can be completed in the 90-min dedicated lab session. However, you can check out a “lab in a box” kit so you can complete the experiments wherever and whenever is convenient for you. 1 The DSP Shield was developed by Prof. Greg Kovacs’ group in collaboration with Texas Instruments. ee264.stanford.edu

EE264 Digital Signal Processing Hands-On Lab Option for Winter … · 2016-10-31 · EE264 Digital Signal Processing Hands-On Lab Option for Winter Quarter! Instructors: Ron Schafer

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Page 1: EE264 Digital Signal Processing Hands-On Lab Option for Winter … · 2016-10-31 · EE264 Digital Signal Processing Hands-On Lab Option for Winter Quarter! Instructors: Ron Schafer

EE264 Digital Signal Processing Hands-On Lab Option for Winter Quarter! Instructors: Ron Schafer and Fernando Mujica

Digital Signal Processing (DSP) is at the heart of almost all modern technology. Applications of signal processing include some of the hottest current technology trends: internet of things (IoT), cloud computing, software-defined radios, robotics, autonomous vehicles, etc.

In EE264 (3 credit hours), you will learn the fundamentals of DSP: • Discrete-time (D-T) random signals • Sampling, reconstruction, D-T filtering, multi-rate systems • Quantization in analog to digital conversion, and oversampling • Properties of linear time invariant (LTI) systems • Quantization effects in fixed-point implementations of filters • Digital filter design • Discrete Fourier Transform (DFT) and FFT • Spectrum analysis using the DFT • Parametric signal modeling

UPDATED EE264 lab option (4 credit hours) This hands-on component will focus on practical implementations of DSP applications on embedded processors. You will have access to an embedded processor board (DSP Shield1) and accessories. The course will be comprised of a few predefined labs to get familiar with the hardware and experiment with the theory discussed in class. For the final project, we will implement an audio-band orthogonal frequency division multiplexing (OFDM) receiver or you can propose your own project (subject to instructor approval). Some possible projects include:

- Acoustic noise suppression - Programmable audio equalizer - Tree-structured subband coding of audio (MP3) - Phase vocoder (aka, a pitch shifter)

- Time/frequency analyzer (spectrogram) - Digital FM/AM communications - OFDM communication link in the audio band - Speech preprocessing for machine learning recognizer

The labs and projects are designed so that they can be completed in the 90-min dedicated lab session. However, you can check out a “lab in a box” kit so you can complete the experiments wherever and whenever is convenient for you. 1 The DSP Shield was developed by Prof. Greg Kovacs’ group in collaboration with Texas Instruments.

ee264.stanford.edu

http://ee264.stanford.edu/