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EE264 Digital Signal Processing



  • LAB component for Winter quarter (4 credit hour option)
    • Sign up for the 4 credit our option for the hands-on practical component (see below)

What is Signal Processing?

Video courtesy of the IEEE Signal Processing Society.

Text Book

  • Discrete-Time Signal Processing, 3/E, Alan V. Oppenheim and Ronald W. Schafer, Pearson, 2010

Course Description

Digital Signal Processing (DSP) is at the heart of almost all modern technology: digital communications, audio/image/video compression, 3D sensing for human machine interfaces and environment perception, multi-touch screens, sensing for health, fitness, biometrics, and security, and the list goes on and on.  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. We are also starting to see higher levels of performance and reduced computational requirements by combining DSP and machine learning techniques.

Oppenheim and Schafer 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

We will use the flipped-classroom format.  Classroom time will focus on deep understanding of concepts and applications via discussions with instructors and guest speakers.

LAB component in Winter quarter (4 credit hour option)

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 DSP Shield is a portable embedded processor board with an easy to use C/C++ development environment very similar to the popular Arduino IDE.  The board also contains an audio codec, which would allow us to explore DSP applications in the audio frequency range.  You will experiment with three of the most common compute resources in DSP systems: a programmable processor, sample by sample hardware acceleratoe and block-based hardware accelerators.

The labs and final project are designed so that they can be completed in the dedicated lab portion of the class.  However, you will have access to a board and all required accessories so you can experiment whenever and wherever is convenient for you!  SCPD students are also welcomed to take the lab portion of the class.

For the final project, you will implement an audio-band orthogonal frequency division multiplexing (OFDM) receiver or you can propose your own project (subject to instructors approval). Some of the projects that has been implemented in the past include:

- Heart rate estimator, Hu
- Guitar effect synthesizer, Herman
- Phase vocoder (pitch shifter), Kong
- Audio compressor and de-esser, Deo

- Time/frequency analyzer (spectrogram), Ling
- Tempo estimation and manipulation, Cheng and Harris
- Speech preprocessing for machine learning recognizer, Chai
- Digital Audio filter for small unmanned aircraft, Krukowski and Hammond

(Project reports courtesy of the corresponding authors)
Energia and DSP Shield

1 The DSP Shield was developed by Prof. Greg Kovacs’ group in collaboration with Texas Instruments.