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Toward Stochastic Realization Theory for Generalized Linear Switched Systems With Inputs: Decomposition Into Stochastic and Deterministic Components and Existence and Uniqueness of Innovation Form
We study a class of stochastic Generalized Linear Switched System (GLSS), which includes subclasses of jump-Markov, piecewise-linear and Linear Parameter-Varying (LPV) systems. We prove that the output of such systems can be decomposed into deterministic and stochastic components. Using this decompo...
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Published in: | IEEE control systems letters 2024-01, Vol.8, p.1841-1846 |
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creator | Rouphael, Elie Mejari, Manas Petreczky, Mihaly Belkoura, Lotfi |
description | We study a class of stochastic Generalized Linear Switched System (GLSS), which includes subclasses of jump-Markov, piecewise-linear and Linear Parameter-Varying (LPV) systems. We prove that the output of such systems can be decomposed into deterministic and stochastic components. Using this decomposition, we show existence of state-space representation in innovation form, and we provide sufficient conditions for such representations to be minimal and unique up to isomorphism. |
doi_str_mv | 10.1109/LCSYS.2024.3417189 |
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subjects | Automatic Engineering Sciences innovation representation Linear systems Stochastic processes stochastic realization theory Switched systems Switches System identification Technological innovation White noise |
title | Toward Stochastic Realization Theory for Generalized Linear Switched Systems With Inputs: Decomposition Into Stochastic and Deterministic Components and Existence and Uniqueness of Innovation Form |
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