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1© 2014 The MathWorks, Inc.
Signal Processing and Analysis with MATLAB
Gabriele Bunkheila
Senior Application Engineer, MathWorks
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Agenda
Manipulate and visualise time-domain data
Gain insight by applying signal transformations
Measure standard signal metrics
Design and apply digital filters
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Signal analysis for classification
Application examples
Mobile sensing
Structural health monitoring (SHM)
Automated trading
Engine event detection
Radar post-processing
Advanced surveillance
...
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Challenges with Signal processing and Analysis
Need domain-specific knowledge
Open-ended problem and long discovery cycles
Bound to fail if done with
the wrong tools
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Example: Human Activity Analysis and Classification
Courtesy of:
Davide Anguita, Alessandro Ghio, Luca Oneto, Xavier Parra and Jorge L. Reyes-Ortiz.
Human Activity Recognition on Smartphones using a Multiclass Hardware-Friendly Support Vector Machine. International
Workshop of Ambient Assisted Living (IWAAL 2012). Vitoria-Gasteiz, Spain. Dec 2012
Dataset available at:
http://archive.ics.uci.edu/ml/datasets/Human+Activity+Recognition+Using+Smartphones
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Human Activity Analysis and Classification
Solution
Only core built-in Signal Processing algorithms
66 high-quality features extracted with only
65 lines of code!
Visualisation and automation
accelerate insight iterations
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Leverage built-in algorithms
How much have I not needed to re-invent?
Signal Processing Toolbox
Neural Network Toolbox
cheby2
filter
rms
pwelch
periodogram
xcov
findpeaks
…
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Summary
MATLAB for Signal Processing and Analysis
Extensive set of de-facto standard functions for
signal processing and analysis
Visualisation and App-driven automation
accelerate insight iterations
Compact and concise language, and
extensive documentation