Digital Signal Processing is the branch of engineering that, in the
space of just a few decades, has enabled unprecedented levels of
interpersonal communication and of on-demand entertainment. By reworking
the principles of electronics, telecommunication and computer science
into a unifying paradigm, DSP is a the heart of the digital revolution
that brought us CDs, DVDs, MP3 players, mobile phones and countless
other devices.
The goal, for students of this course, will be to learn the fundamentals
of Digital Signal Processing from the ground up. Starting from the
basic definition of a discrete-time signal, we will work our way through
Fourier analysis, filter design, sampling, interpolation and
quantization to build a DSP toolset complete enough to analyze a
practical communication system in detail. Hands-on examples and
demonstration will be routinely used to close the gap between theory and
practice.
To make the best of this class, it is recommended that you are
proficient in basic calculus and linear algebra; several programming
examples will be provided in the form of Jupyter notebooks but you can
use your favorite programming language to test the algorithms described
in the course.
- Professor: Paolo Prandoni
- TA: Karen Adam
- TA: Eric Bezzam