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Nonlinear modeling of PEMFC based on fractional order subspace identification

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0 Published in 2019 at "Asian Journal of Control"

DOI: 10.1002/asjc.2092

Abstract: Aiming at the multivariable, nonlinear and fractional‐order characteristics of proton exchange membrane fuel cell (PEMFC), this paper presents a nonlinear state space model based on a novel fractional Hammerstein model subspace identification theory. To reduce… read more here.

Keywords: fractional order; subspace identification; model; order ... See more keywords

Subspace identification for closed-loop 2-D separable-in-denominator systems

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0 Published in 2017 at "Multidimensional Systems and Signal Processing"

DOI: 10.1007/s11045-016-0427-y

Abstract: Identification for closed-loop two-dimensional (2-D) causal, recursive, and separable-in-denominator (CRSD) systems in the Roesser form is discussed in this study. For closed-loop 2-D CRSD systems, under feedback control condition, there exists some correlation between the… read more here.

Keywords: identification; identification closed; closed loop; subspace identification ... See more keywords

Subspace Identification Based Modeling and Control of Batch Particulate Processes

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0 Published in 2017 at "Industrial & Engineering Chemistry Research"

DOI: 10.1021/acs.iecr.7b00682

Abstract: This paper addresses the problem of subspace-based model identification and predictive control of particulate process subject to uncertainty and time-varying parameters. To this end, subspace identification techniques are first adapted to handle the batch nature… read more here.

Keywords: subspace identification; control; particulate; subspace ... See more keywords

Modeling behaviorally relevant neural dynamics enabled by preferential subspace identification

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0 Published in 2020 at "Nature Neuroscience"

DOI: 10.1038/s41593-020-00733-0

Abstract: Neural activity exhibits complex dynamics related to various brain functions, internal states and behaviors. Understanding how neural dynamics explain specific measured behaviors requires dissociating behaviorally relevant and irrelevant dynamics, which is not achieved with current… read more here.

Keywords: neural dynamics; subspace identification; preferential subspace; relevant neural ... See more keywords

Detectability conditions for output-only subspace identification

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0 Published in 2019 at "Mathematical and Computer Modelling of Dynamical Systems"

DOI: 10.1080/13873954.2019.1701038

Abstract: ABSTRACT The scope of output-only/blind identification is restricted to stochastic/statistical processes, but for the first time in this study, the detectability conditions for general output-only subspace identification are investigated. This aids the range of input… read more here.

Keywords: subspace identification; output subspace; output; detectability conditions ... See more keywords

Subspace Identification of Distributed Clusters of Homogeneous Systems

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0 Published in 2017 at "IEEE Transactions on Automatic Control"

DOI: 10.1109/tac.2016.2555961

Abstract: This note studies the identification of a network comprised of interconnected clusters of LTI systems. Each cluster consists of homogeneous dynamical systems, and its interconnections with the rest of the network are unmeasurable. A subspace… read more here.

Keywords: lti systems; subspace identification; distributed clusters; identification distributed ... See more keywords

Tensor Nuclear Norm LPV Subspace Identification

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1 Published in 2018 at "IEEE Transactions on Automatic Control"

DOI: 10.1109/tac.2018.2800772

Abstract: Linear parameter varying (LPV) subspace identification methods suffer from an exponential growth in number of parameters to estimate. This results in problems with ill-conditioning. In literature, attempts have been made to address the ill-conditioning by… read more here.

Keywords: lpv subspace; nuclear norm; tensor nuclear; subspace identification ... See more keywords

Projection domain processing for low-dose CT reconstruction based on subspace identification.

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0 Published in 2022 at "Journal of X-ray science and technology"

DOI: 10.3233/xst-221262

Abstract: PURPOSE Low-dose computed tomography (LDCT) has promising potential for dose reduction in medical applications, while suffering from low image quality caused by noise. Therefore, it is in urgent need for developing new algorithms to obtain… read more here.

Keywords: projection; subspace identification; based subspace; low dose ... See more keywords