DSP_Project

Repo to contain all the work we do for the DSP project at the University of Utah

Project PDF. Still working on this for others who may come here in the future

Link to the pdf

Commit from Miguel to start the repo

Link to the Piazza post

Link to octave band filtering PDF

Link to the Z-transform stuff from piazza

NOTE!!!

You must first add the util directory to /LabP14_Exercise5/pythonStuff/ BEFORE running any of the python code!! This was accidentally left out of the pythonStuff directory and is crucial to the execution of all code calling the setup of the filters!!

requirements

must have the following installed python libs, shown under the program

Run testOBF.py

• running tesOBF.py will call the filter class and sets things up. will call to calc coeffs and then apply the filter to data.

python3 testOBF.py

pip install numpy matplotlib rich

## Run create_FIR_filter.py - running create_FIR_filter.py like shown below will show the help option. ~ ~python3 create_FIR_filter.py -h~ ~ ~~ - example run with 32 elements and fmin=2, fmax=8 ~ ~python3 create_FIR_filter.py -N 32 -F 2 8~ ~ ~~

Run create_FIR_filter.py

• running Create_FIR_FIlter_Example.py

python3 Create_FIR_FIlter_Example.py

Run testOBF.py

• running test_audio_input.py will call the filter class and sets things up, then start attempting to read from a default mic. may not work exactly since the thresholds are dependent on my default, but worth a shot if you want to take a look. will call to calc coeffs and then apply the filter to data live as it comes through the mic.

python3 test_audio_input.py

pip install numpy matplotlib rich pyaudio

this is another version of the above.

python3 live_audio_vis.py

pip install numpy matplotlib pyaudio