Python代写 - Digital Signal processing: IIR fifilters
This assignment covers IIR filters.
Your task is to solve a problem which requires realtime filtering
of a physical quantity.
You have two options for the data acquisition:
• Buy an Arduino. They work under Windows, Mac and Linux. They
have a sampling rate of 100 Hz.
• If you don’t want to spend any money you can use your webcam as an
RGB colour sensor, sampling at its frame rate.
Every team needs to have a different application for their measurement.
Think of something simple such as measuring the speed of a fan with an LDR
or the webcam. Perhaps you have a fishtank and you’d like to know how often
a fish swims past. Or if the flowerpot is watered. Add your topic to the wiki
provided on moodle as soon as possible. It needs to solve a practical real life
problem and require low, high, bandpass or bandstop filtering. Excessive use
of identical topics will result in low marks.
Again you work in teams of two students and one report is submitted per
1. Present a realtime measurement problem to be solved which requires
filtering. For example noise needs to be removed or a signal needs to be
detected. Marks are given for initiative, inventiveness and originality
(= ideas which haven’t come straight from the lecturer, lab demonstrators or other groups). Document the experiment with (all compulsory):
• photos of the setup
• dataflow diagrams
• YouTube clip(s)
in addition to your report. How would you like to present the results?
Just as a plot or perhaps a bar graph? QT for Python might be an
option to look into. [20%]
2. Check the sampling rate of your acquisition by running it for example
for 10secs and check against the number of samples expected. How
could you check for jitter in the sampling? [20%]
3. Determine the filter response(s) which are required and justify them.
Generate the SOS coefficients for the filter(s) either with the help of
Python’s high level functions or analytical solutions shown in the lecture. [20%]
4. Write two classes:
(a) IIR2Filter which implements a 2nd order IIR filter which takes
the coefficients in the constructor and has a method called:
where y and x are simple scalars (no arrays) as usual. Optimise
this class that it won’t need any arrays for its buffers and coeffi-
(b) a class IIRFilter which directly takes the SOS array from the
high level IIR design commands as its constructor argument and
which then creates a chain of 2nd order filter instances of IIR2Filter
classes. Thus they form an array of instances of IIR2Filter. Again
implement a function which then filters the signal:
and then internally processes the data x by sending it through
the chain of 2nd order IIR2Filter classes. Implement the filtering operation again in the most effective way by not using index
5. Compare your filtered results with the original recordings, show both
signals in a realtime demo (YouTube clip) and discuss if you have been
successful. Do a critical analysis. [10%]
High level design commands are allowed such as “butter” but the actual
IIR filtering operations need be written from scratch as outlined above. Any
use of “lfilter”, “conv” or other high level python filter operation will result
again in zero marks. Proof of realtime processing in form of a video needs
to be given and the video needs to show clearly what it’s about. Please add
your link to the wiki and also add a readme to your zip containing all the
The code needs to be again submitted as a zip file and it will be tested if
it runs. Crashing code will result in low marks.
As before I expect sharp figures in vector format in the report. The
complete code needs to be in the appendix and also uploaded to moodle.
Since this task is more difficult also to coordinate in a distributed team
there is more time to finish it.
Deadline for the report is 7th Dec.