L. Rankine, M. Mesbah, and B. Boashash (Australia)
Structural Complexity, Electroencephalogram
Atomic decomposition has been a popular tool for ex
tracting information about localised signal structures.
This is a direct consequence of incorporating redun
dant time-frequency and time-scale dictionaries for sig
nal decomposition. In this paper, we propose a mea
sure of signal complexity related to a given decompo
sition dictionary and based on the number of atoms
needed to represent the signal. This measure is di
rectly extracted from the atomic decomposition and
one of the potential applications is the detection of
changes in signal structure. For example, automatic
newborn EEG seizure detection can be achieved by
detecting the change in signal structure as the EEG
changes from the background state to the seizure state.
This complexity measure is evaluated using two atomic
decomposition methods; namely Basis Pursuit (BP)
and Matching Pursuit (MP).