Results 261 to 270 of about 35,609 (308)

Difference Subspace and Its Generalization for Subspace-Based Methods

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015
Subspace-based methods are known to provide a practical solution for image set-based object recognition. Based on the insight that local shape differences between objects offer a sensitive cue for recognition, this paper addresses the problem of extracting a subspace representing the difference components between class subspaces generated from each set
Kazuhiro Fukui
exaly   +3 more sources

Nonstationary Consistency of Subspace Methods

IEEE Transactions on Automatic Control, 2007
In this paper, we study ldquononstationary consistencyrdquo of subspace methods for eigenstructure identification, i.e., the ability of subspace algorithms to converge to the true eigenstructure despite nonstationarities in the excitation and measurement noises. Note that such nonstationarities may result in having time-varying zeros for the underlying
A Benveniste, Laurent Mevel
exaly   +2 more sources

On Consistency of Subspace Methods for System Identification

Automatica, 1998
The authors consider consistency of subspace methods for system identification. They give conditions ensuring consistency of the subspace methods used in subspace identification methods. For systems without noise, a persistence of excitation condition on the input signal can ensure the consistency. Moreover, the authors give a system for which subspace
Magnus Jansson, Bo Wahlberg
exaly   +3 more sources

Realization of stable models with subspace methods

Automatica, 1996
The paper deals with estimating the dynamics of stable linear state-space systems by stable approximants of the models computed from the least-squares approach. Either asymptotic or marginal stability is taken into account for the approximate model. In the first stage, the shift invariance approach is used where the system matrix is recovered from the ...
J M Maciejowski
exaly   +2 more sources

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

Subspace methods for robot vision

IEEE Transactions on Robotics and Automation, 1996
In contrast to the traditional approach, visual recognition is formulated as one of matching appearance rather than shape. For any given robot vision task, all possible appearance variations define its visual workspace. A set of images is obtained by coarsely sampling the workspace.
Shree K. Nayar, Sameer A. Nene, Hiroshi Murase   +2 more
openaire   +1 more source

Boosting random subspace method

Neural Networks, 2008
In this paper we propose a boosting approach to random subspace method (RSM) to achieve an improved performance and avoid some of the major drawbacks of RSM. RSM is a successful method for classification. However, the random selection of inputs, its source of success, can also be a major problem.
Nicolás García-Pedrajas, Domingo Ortiz-Boyer   +1 more
openaire   +3 more sources

Subspace methods for computational relighting

SPIE Proceedings, 2013
We propose a vector space approach for relighting a Lambertian convex object with distant light source, whose crucial task is the decomposition of the reflectance function into albedos (or reflection coefficients) and lightings based on a set of images of the same object and its 3-D model.
Ha Q. Nguyen 0001, Siying Liu, Minh N. Do   +2 more
openaire   +1 more source

The subspace method in Hilbert space

Systems and Computers in Japan, 2001
AbstractThe subspace method has usually been applied to a multidimensional space (i.e., feature space) which uses features as its basis. A subspace method can also be applied to a functional space, since the subspace can be defined by an arbitrary linear space. This paper proposes the mapping of a feature space onto the Hilbert subspace so that pattern
openaire   +1 more source

On Moment Methods in Krylov Subspaces

Doklady Mathematics, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
openaire   +2 more sources