A review of the expectation maximization algorithm in data-driven process identification
Abstract The Expectation Maximization (EM) algorithm has been widely used for parameter
estimation in data-driven process identification. EM is an algorithm for maximum likelihood …
estimation in data-driven process identification. EM is an algorithm for maximum likelihood …
A survey on switched and piecewise affine system identification
Recent years have witnessed a growing interest on system identification techniques for
switched and piecewise affine models. These model classes have become popular not only …
switched and piecewise affine models. These model classes have become popular not only …
Identification of switched linear systems via sparse optimization
L Bako - Automatica, 2011 - Elsevier
The work presented in this paper is concerned with the identification of switched linear
systems from input-output data. The main challenge with this problem is that the data are …
systems from input-output data. The main challenge with this problem is that the data are …
A piecewise linear regression and classification algorithm with application to learning and model predictive control of hybrid systems
A Bemporad - IEEE Transactions on Automatic Control, 2022 - ieeexplore.ieee.org
This article proposes an algorithm for solving multivariate regression and classification
problems using piecewise linear predictors over a polyhedral partition of the feature space …
problems using piecewise linear predictors over a polyhedral partition of the feature space …
Data-driven modeling for river flood forecasting based on a piecewise linear ARX system identification
Most of the studies related to the rainfall-runoff modeling of rivers consist of data-driven
models, given that the corresponding physical modeling approaches are based on a …
models, given that the corresponding physical modeling approaches are based on a …
Piecewise affine regression via recursive multiple least squares and multicategory discrimination
In nonlinear regression choosing an adequate model structure is often a challenging
problem. While simple models (such as linear functions) may not be able to capture the …
problem. While simple models (such as linear functions) may not be able to capture the …
Online identification of piecewise affine systems using integral concurrent learning
Piecewise affine (PWA) systems are attractive models that can represent various hybrid
systems with local affine subsystems and polyhedral regions due to their universal …
systems with local affine subsystems and polyhedral regions due to their universal …
Learning linear complementarity systems
This paper investigates the learning, or system identification, of a class of piecewise-affine
dynamical systems known as linear complementarity systems (LCSs). We propose a …
dynamical systems known as linear complementarity systems (LCSs). We propose a …
Tracking switched dynamic network topologies from information cascades
Contagions, such as the spread of popular news stories, or infectious diseases, propagate in
cascades over dynamic networks with unobservable topologies. However,“social signals,” …
cascades over dynamic networks with unobservable topologies. However,“social signals,” …
A variational Bayesian approach to robust identification of switched ARX models
Y Lu, B Huang, S Khatibisepehr - IEEE transactions on …, 2015 - ieeexplore.ieee.org
A variational Bayesian approach to robust identification of switched auto-regressive
exogenous models is developed in this paper. By formulating the problem of interest under a …
exogenous models is developed in this paper. By formulating the problem of interest under a …