Results 261 to 270 of about 27,115 (309)

Subspace linear inverse method

Inverse Problems, 1994
The paper describes a numerical algorithm for the iterative solution of large scale linear inverse problems. From optimization point of view weighted least squares subject to parameters which are compatible with the data are used to find approximate solutions of linear inverse problems.
Oldenburg, Douglas W., Li, Yaoguo
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From the Subspace Methods to the Mutual Subspace Method

2010
The Subspace Method [25, 21] is a classic method of pattern recognition, and has been applied to various tasks. The Mutual Subspace Method [19] is an extension of the Subspace Methods, in which canonical angles (principal angles) between two subspaces are used to define similarity between two patterns (or two sets of patterns). The method is applied to
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Projection Methods in Krylov Subspaces

Journal of Mathematical Sciences, 2019
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Error-Minimizing Krylov Subspace Methods

SIAM Journal on Scientific Computing, 1994
This paper first introduces generalized conjugate gradient methods which specialize to error minimizing procedures as well as to residual minimizing methods. General minimum error methods are then introduced, and the two method classes are compared.
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Fast subspace-based source localization methods

2008 5th IEEE Sensor Array and Multichannel Signal Processing Workshop, 2008
Source localization is based on the spectral matrix algebraic properties. Propagator, and Ermolaev-Gershman (EG) noneigenvector algorithms exhibit a low computational load. Propagator is based on spectral matrix partitioning. EG algorithm obtains an approximation of noise subspace using an adjustable power parameter of the spectral matrix and choosing ...
Marot, Julien, Fossati, Caroline, Bourennane, Salah   +2 more
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Subspace identification methods and fMRI analysis

2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2008
The main goal of this paper is to propose application of modern multidimensional systems identification algorithms of the subspace identification theory in the context of fMRI data analysis. The methods originated in 1990s in the field of process control and identification and yield robust linear model parameter estimates for systems with many inputs ...
Jana, Tauchmanova, Martin, Hromcik
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Macromodelling oscillators using krylov-subspace methods

Asia and South Pacific Conference on Design Automation, 2006., 2006
We present an efficient method for automatically extracting unified amplitude/phase macromodels of arbitrary oscillators from their SPICE-level circuit descriptions. Such comprehensive oscillator macromodels are necessary for accuracy when speeding up simulation of higher-level circuits/systems, such as PLLs, in which oscillators are embedded. Standard
Xiaolue Lai, Jaijeet Roychowdhury
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On Moment Methods in Krylov Subspaces

Doklady Mathematics, 2020
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Admissible subspaces and the subspace iteration method

BIT Numerical Mathematics
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Least Squares Methods in Krylov Subspaces

Journal of Mathematical Sciences, 2017
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