Subspace Algorithms
Mostrando 1-7 de 7 artigos, teses e dissertações.
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1. A new block algorithm for full-rank solution of the Sylvester-observer equation
A new block algorithm for computing a full rank solution of the Sylvester-observer equation arising in state estimation is proposed. The major computational kernels of this algorithm are: 1) solutions of standard Sylvester equations, in each case of which one of the matrices is of much smaller order than that of the system matrix and (furthermore, this small
Publicado em: 2011
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2. Subspace predictive control. / Controle preditivo com enfoque em subespaços.
Model Predictive Control (MPC) technology is widely used in chemical process industries. Subspace identification (SID) on the other hand has proven to be an efficient alternative for classical system identification methods. Based on the results from MPC and SID, it was developed in the late 90s a new control approach, called Subspace Predictive Control (SPC)
Publicado em: 2009
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3. Metodos de subespaços para identificação de sistemas : propostas de alterações, implementações e avaliações / Subspace methods for systems identification : proposals of alterations, implementations and evaluations
This study presents the theoretical foundations of multivariable data modeling in state space by Subspace Methods for Systems Identification of linear time invariant, discrete time, systems. The work contains some basic concepts of dynamic systems, a little of history and the elements of systems identification, state space models and extended state space mod
Publicado em: 2008
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4. Identificação e controle estocasticos descentralizados de sistemas interconectados multivariaveis no espaço de estado
In this thesis a decentralized methodology for linear state space identification of discrete time, serially interconnected multivariable stochastic systems is proposed. The global system identificationis achieved by means of the individual identification of its subsystems through some state space methods for identification of multivariable systems and time s
Publicado em: 2005
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5. Dimensionality reduction using mean conditional entropy applied for bioinformatics and image processing problems / "Redução de dimensionalidade utilizando entropia condicional média aplicada a problemas de bioinformática e de processamento de imagens"
Dimensionality reduction is a very important pattern recognition problem with many applications. Among the dimensionality reduction techniques, feature selection was the main focus of this research. In general, most dimensionality reduction methods that may be found in the literature privilegiate cases in which the data is linearly separable and with only tw
Publicado em: 2004
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6. PARAMETRIC IDENTIFICATION OF MECHANICAL SYSTEMS USING SUBSPACE ALGORITHMS / IDENTIFICAÇÃO PARAMÉTRICA DE SISTEMAS MECÂNICOS USANDO ALGORITMOS DE SUBESPAÇO
Parametric identification of mechanical systems is one of the main applications of the system identification techniques in Mechanical Engineering, specifically for the identification of modal parameters of flexible structures. One of the main problems in the identification is the presence of noise in the measurements. This work presents an analysis in the pr
Publicado em: 2003
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7. Tecnicas de identificação modal multivariavel orientadas a subespaços
The analysis oí the dynamical behaviour oí structures is oí great economical and technological importance. The present work brings a contribution to this field, presenting time domam identification methods based on rea1ization theory. The methods are implemented for multivariable measurements through the use of the subspace approách. Numerical simulation
Publicado em: 2003