Results 261 to 270 of about 13,903 (307)

DIA-Estimator and Multidimensional Model Misspecifications: GNSS-based Positioning Safety Analysis for UAV. [PDF]

GPS Solut
Ciuban S, Teunissen PJG, Tiberius CCJM.
europepmc   +1 more source

CiCLoDS: Joint cell clustering and gene selection for single-cell spatial transcriptomics. [PDF]

Sci Rep
Wang N, He Y, Ray E, Won KJ, Cetrulo CL, Li D, Moore JH, Zhang S, Huang X.   +8 more
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An overview of subspace identification

Computers and Chemical Engineering, 2006
This paper provides an overview of the state of the art of subspace identification methods for both open-loop and closed-loop systems. Practical considerations and future directions are given at the end of the paper.
S Joe Qin
exaly   +2 more sources

System Identification Based on Invariant Subspace

IEEE Transactions on Automatic Control, 2022
This paper proposes a novel system identification method based on the notion of invariant subspace. It is shown that when the system input and output asymptotically converge onto an invariant subspace, a new form of regression can be obtained. New identification algorithms are then developed based on the obtained regression.
Chao Huang 0018, Gang Feng 0001, Hao Zhang 0008, Zhuping Wang   +3 more
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On-line subspace identification

2001 European Control Conference (ECC), 2001
In this paper a recursive technique, based on the subspace state space identification methods, is presented for identification of time-varying systems. The main idea was to develop an iterative algorithm with most of the advantages of this kind of methods in order to deal with real-time applications and minimize the computational burden.
Catarina J. M. Delgado, P. Lopes dos Santos, J. L. Martins de Carvalho   +2 more
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Probing inputs for subspace identification

Proceedings of the 39th IEEE Conference on Decision and Control (Cat. No.00CH37187), 2002
There is experimental evidence that the standard subspace methods (e.g. the N4SID method) perform poorly in certain conditions where the past signals (past inputs and past outputs) and future input spaces are nearly parallel. Based on an elementary numerical conditioning analysis, the paper describes a class of (system-dependent) input signals (called ...
CHIUSO, ALESSANDRO, PICCI, GIORGIO
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A framework for subspace identification methods

Proceedings of the 2001 American Control Conference. (Cat. No.01CH37148), 2001
Similarities and differences among various subspace identification methods (MOESP, N4SID and CVA) are examined by putting them in a general regression framework. Subspace identification methods consist of three steps: estimating the predictable subspace for multiple future steps, then extracting state variables from this subspace and finally fitting ...
Ruijie Shi, John F. MacGregor
openaire   +1 more source