Code for Webinar "Signal Processing and Machine Learning Techniques for Sensor Data Analytics"
Updated 10 May 2016
These files contain all the code necessary to run the example in the Webinar "Signal Processing and Machine Learning Techniques for sensor Data Analytics". They also include code to automate the download and preparation of the dataset used.
In that webinar (http://www.mathworks.com/videos/signal-processing-and-machine-learning-techniques-for-sensor-data-analytics-107549.html) we presented an example of a classification system able to identify the physical activity that a human subject is engaged in, based on the accelerometer signals generated by his or her smartphone. We discussed signal processing methods to extract highly-descriptive features, and we gave an overview of a number of techniques to choose and train a classification algorithm. Along the way we demonstrated the use of Parallel Computing to accelerated the extraction of features from a large dataset.We also presented a workflow to transition signal processing and predictive algorithms to embeddable software implementations - first using DSP system modelling, and then automatically generating C/C++ source code directly from MATLAB.
Gabriele Bunkheila (2021). Code for Webinar "Signal Processing and Machine Learning Techniques for Sensor Data Analytics" (https://www.mathworks.com/matlabcentral/fileexchange/53001-code-for-webinar-signal-processing-and-machine-learning-techniques-for-sensor-data-analytics), MATLAB Central File Exchange. Retrieved .
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