Overview
Syllabus
Intro
Motivation
Data collection
Equations of motion
Free vibration
Modal analysis techniques
Sampling model
Joint sparse frequency estimation
Classical spectral estimation
Method #1: Proper Orthogonal Decomposition
SVD of data matrix
POD considerations
Minimum separation condition
Uniform time sampling
Experiment: Telegraph Bridge data
Experiment, ctd
Method #2: Atomic norm minimization
Synchronous random sampling
Random temporal compression
Random spatial compression
Benefits of compression
Sampling rate scaling
Orthogonality
Synchronous vs. asynchronous
More sensors
Open questions
Taught by
Alan Turing Institute