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This repo holds a real-time implementation of the MUSIC algorithm
written in C for the Beaglebone Black/Green.  MUSIC is short for
"multiple signal classification", and is a well-known signal
processing algorithm used for estimating the frequency of an input
sinusoid in the presence of noise, and also for direction finding in
radar. Details of the algorithm are provided on Wikipedia:
https://en.wikipedia.org/wiki/MUSIC_(algorithm)  
My program estimates the frequency of an input real-time signal -- it
reads data from the 
ADC-001 audio experimenter's cape,
https://github.com/brorson/ADC-001_hardware_information 
and prints the estimated frequency of the input signal to the
Beaglebone console at a rate of a few Hz.

The code
assumes your Beaglebone runs the "Debian 9.2 2017-10-10 4GB SD IoT"
image, available here:  https://beagleboard.org/latest-images.  A
description of how to burn this image into your Beaglebone is included
in this directory.  The code may run on other versions, but I have not
tested it.

My implementation uses the numerical libraries BLAS and LAPACK,
which I have built and downloaded to the Beaglebone.  A description of
how load BLAS and LAPACK onto your Beaglebone is provided in this
directory.  In the lib subdirectory I have placed pre-built images of
the required libraries which you can load onto your Beaglebone to use
this program.

Stuart Brorson
1.9.2018