@inproceedings{1a9f073db6cc4b3bbad4976ee6ea3ec8,
title = "Nonlinear system identification using compressed sensing",
abstract = "This paper describes an approach to system identification based on compressive sensing and demonstrates its efficacy on a challenging classical benchmark single-input, multiple output (SIMO) mechanical system consisting of an inverted pendulum on a cart. The differential equations describing the system dynamics are to be determined from measurements of the system's input-output behavior. These equations are assumed to consist of the superposition, with unknown weights, of a small number of terms drawn from a large library of nonlinear terms. Under this assumption, compressed sensing allows the constituent library elements and their corresponding weights to be identified by decomposing a time-series signal of the system's outputs into a sparse superposition of corresponding time-series signals produced by the library components.",
keywords = "Basis Pursuit, Compressed Sensing, Inverted Pendulum, Non-Linear, Sparsity, System Identification",
author = "Manjish Naik and Douglas Cochran",
year = "2012",
doi = "10.1109/ACSSC.2012.6489039",
language = "English (US)",
isbn = "9781467350518",
series = "Conference Record - Asilomar Conference on Signals, Systems and Computers",
pages = "426--430",
booktitle = "Conference Record of the 46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012",
note = "46th Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2012 ; Conference date: 04-11-2012 Through 07-11-2012",
}