I teach digital signal processing
to seniors and graduate students at the University of Minnesota.
What is digital signal processing? Let me give you an example.
A pacemaker uses signal processing
to detect abnormalities in an electrocardiogram or ECG
from the heart in order to deliver a shock
when needed. The most exciting thing about DSP or digital signal processing
is it's
such a powerful technology that can be used everywhere.
If you are storing your images from a camera in JPEG format,
that saves ten times the number of bits or fifty times the number of bits
compared to a bitmap image.
If you are watching TV, the TV station is
sending an encoded version that is decoded at the TV in the receiver in
the TV.
So DSP is key to all technologies whether it is a cell phone
or telephone lines, or transmitting
hundreds of gigabytes of data through fiber cables
that go underneath the oceans. And again
transmitting data at those rates requires a lot of signal processing.
This important technology is used everywhere
in applications such as wired and wireless communication systems
storage, coding and decoding
speech, audio, image
and video processing. It is an integral part of modems
TVs and cameras. Other examples include predicting earthquakes
from seismic signals and in analyzing biomedical signals and images.
My class involves a lot of Math
and it's easy for students to lose sight of these real world applications.
In a typical digital signal processing class, the professor
writes equations from one end of the board to the other and students spend
class time copying notes.
They do not typically work on programming assignments
that would help them understand how the math
relates to the processing of signals. Like many engineering professors
I used to write down a lot of equations on the board
or flip through power point slides and
pause to ask if there were questions, but I
changed my teaching style because I want my students to relate math
to real-world applications. Starting in fall 2013
I moved my class to an active learning class room.
Now I set aside fifteen minutes for every class
for students to work in groups. Students work in groups of two or three
to solve problems or take a quiz. They also work on MATLAB experiments
as part of group activity or quiz.I also changed how I deliver
content.
I distribute power point slides of my lecture before the class.
During the class I use PowerPoint slides
to quickly go through easy concepts. However I take the time to explain
more difficult concepts by writing down every step on paper
under a camera that was displayed to the the entire class.
I also run MATLAB code in class
to demonstrate filtering of audio sounds.
This approach
has freed up
extra time for group work. My students
reacted positively to my demonstrating the experiments.
It got them engaged. It really helped them understand
the implications of the math that they were seeing
through these experiments. This approach to delivering content
and having students work together and share their results
helps students develop intuitive insight
into signal processing.