Results 11 to 20 of about 3,247,690 (230)

Data-Driven Predictive Control of Exoskeleton for Hand Rehabilitation with Subspace Identification [PDF]

open access: yesSensors, 2022
This study proposed a control method, a data-driven predictive control (DDPC), for the hand exoskeleton used for active, passive, and resistive rehabilitation. DDPC is a model-free approach based on past system data.
Erkan Kaplanoglu, Gazi Akgun
doaj   +2 more sources

On subspace system identification methods [PDF]

open access: yesModeling, Identification and Control, 2022
An open and closed loop subspace system identification algorithm DSRe is compared to competitive open loop algorithms, DSR, and N4SID. Additionally, DSRe is compared vs the optimal Prediction Error Method (PEM).
Christer Dalen, David Di Ruscio
doaj   +2 more sources

Closed Loop Subspace Identification [PDF]

open access: yesModeling, Identification and Control, 2005
A new three step closed loop subspace identifications algorithm based on an already existing algorithm and the Kalman filter properties is presented. The Kalman filter contains noise free states which implies that the states and innovation are uneorre ...
Geir W. Nilsen, David Di Ruscio
doaj   +2 more sources

Hyperspectral Subspace Identification [PDF]

open access: yesIEEE Transactions on Geoscience and Remote Sensing, 2008
Signal subspace identification is a crucial first step in many hyperspectral processing algorithms such as target detection, change detection, classification, and unmixing. The identification of this subspace enables a correct dimensionality reduction, yielding gains in algorithm performance and complexity and in data storage.
Bioucas-Dias, José M., Nascimento, Jose
openaire   +4 more sources

Modal parameters identification of bridge by improved stochastic subspace identification method with Grubbs criterion

open access: yesMeasurement + Control, 2021
In the wind tunnel test of a long-span bridge model, to ensure that the dynamic characteristics of the model can satisfy the test design requirements, it is particularly important to accurately identify the modal parameters of the model.
Yulin Zhou   +5 more
doaj   +2 more sources

Subspace-Based Identification of Nonlinear Structures [PDF]

open access: yesShock and Vibration, 2008
Conventional linear estimators give results contaminated in presence of nonlinearities and the extraction of underlying linear system properties is thus difficult. To overcome this problem, the implementation of a recently developed method, called Nonlinear Subspace Identification (NSI), is considered in this paper, by using the perspective of ...
S. Marchesiello, L. Garibaldi
doaj   +4 more sources

Linear parameter-varying subspace identification: A unified framework [PDF]

open access: yesAutomatica, 2021
In this paper, we establish a unified framework for subspace identification (SID) of linear parameter-varying (LPV) systems to estimate LPV state-space (SS) models in innovation form. This framework enables us to derive novel LPV SID schemes that are extensions of existing linear time-invariant (LTI) methods. More specifically, we derive the open-loop,
Cox, Pepijn Bastiaan, Tóth, Roland
openaire   +4 more sources

Subspace system identification

open access: yesIranian Journal of Electrical and Electronic Engineering, 2005
We give a general overview of the state-of-the-art in subspace system identification methods. We have restricted ourselves to the most important ideas and developments since the methods appeared in the late eighties.
J. Poshtan, H. Mojallali
doaj   +1 more source

Understanding Stochastic Subspace Identification [PDF]

open access: yes, 2006
The data driven Stochastic Subspace Identification techniques is considered to be the most powerful class of the known identification techniques for natural input modal analysis in the time domain. However, the techniques involves several steps of "mysterious mathematics" that is difficult to follow and to understand for people with a classical ...
Andersen, Palle, Brincker, Rune
core   +3 more sources

Robust subspace structure discovery for cell type identification in scRNA-seq data [PDF]

open access: yesBMC Bioinformatics
Single-cell RNA sequencing (scRNA-seq) technology has transformed gene expression studies by enabling analysis at the individual cell level, offering unprecedented insights into cellular heterogeneity.
Xianyong Zhou   +6 more
doaj   +2 more sources

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