EE264 Digital Signal Processing

Winter Quarter 2015 

Instructors: Ron Schafer and Fernando Mujica

Announcements

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.

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.

NEW in Winter 2015 is EE264 (4 credit hour option)

This hands-on component will focus on practical implementations of DSP applications on embedded processors.  For the final project, you will implement a relevant DSP application in fields such as audio signal processing and communications.  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 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 have access to a board and all required accessories so you can experiment whenever and wherever is convenient for you!
For the final project, you can choose a project from the list below or propose your own (subject to instructors appraval):

- 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


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