Open AccessPartitioning continuous segmented signals
Author(s) -
Amar A.,
BenSultan S.,
Atias C.
Publication year - 2014
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2014.0951
Subject(s) - segmentation , polynomial , signal (programming language) , constraint (computer aided design) , algorithm , computer science , line (geometry) , mathematics , line segment , pattern recognition (psychology) , mathematical optimization , artificial intelligence , mathematical analysis , geometry , programming language
An off‐line segmentation of a continuous‐time signal is proposed, which changes at unknown transition times and where each segment is modelled as a polynomial with known order but unknown parameters. A model order method based on the maximum likelihood principle is suggested, by imposing the constraint that the complete signal is continuous, for jointly determining the number of segments, the transition times and the parameters of each polynomial. Simulation results show that the proposed approach outperforms the unconstrained segmentation.