- NEW in Winter 2015 is EE264 (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.
- Discrete-Time Signal Processing, 3/E, Alan V. Oppenheim and Ronald W. Schafer, Pearson, 2010
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
|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)
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 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 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