scholarly journals Subspace Methods

2019 ◽  
pp. 267-291
Author(s):  
Tom Boot ◽  
Didier Nibbering
Keyword(s):  
Subspace Methods

Comparison between DOA Estimation Subspace methods for incoherent and coherent signals

2015 ◽  
Vol 1 ◽  
pp. 18
Author(s):  
Ahmed Abdalla ◽  
Suhad Mohammed ◽  
Tang Bin ◽  
Jumma Mary Atieno ◽  
Abdelazeim Abdalla
Keyword(s):  
Linear Array ◽  
Doa Estimation ◽  
Far Field ◽  
Matlab Simulation ◽  
Subspace Methods ◽  
Coherent Signals ◽  
Uniform Linear Array ◽  
Pros And Cons ◽  
Basic Concepts ◽  
And Performance

This paper considers the problem of estimating the direction of arrival (DOA) for the both incoherent and coherent signals from narrowband sources, located in the far field in the case of uniform linear array sensors. Three different methods are analyzed. Specifically, these methods are Music, Root-Music and ESPRIT. The pros and cons of these methods are identified and compared in light of different viewpoints. The performance of the three methods is evaluated, analytically, when possible, and by Matlab simulation. This paper can be a roadmap for beginners in understanding the basic concepts of DOA estimation issues, properties and performance.

scholarly journals Krylov subspace methods for estimating operator-vector multiplications in Hilbert spaces

2021 ◽  
Author(s):  
Yuka Hashimoto ◽  
Takashi Nodera
Keyword(s):  
Krylov Subspace ◽  
Time Series Data ◽  
Linear Equations ◽  
Transfer Operator ◽  
Krylov Subspace Methods ◽  
Krylov Subspace Method ◽  
Linear Operators ◽  
Series Data ◽  
Subspace Method ◽  
Subspace Methods

AbstractThe Krylov subspace method has been investigated and refined for approximating the behaviors of finite or infinite dimensional linear operators. It has been used for approximating eigenvalues, solutions of linear equations, and operator functions acting on vectors. Recently, for time-series data analysis, much attention is being paid to the Krylov subspace method as a viable method for estimating the multiplications of a vector by an unknown linear operator referred to as a transfer operator. In this paper, we investigate a convergence analysis for Krylov subspace methods for estimating operator-vector multiplications.

scholarly journals Krylov Subspace Methods in Dynamical Sampling

2016 ◽  
Vol 15 (1) ◽  
pp. 9-20
Author(s):  
Akram Aldroubi ◽  
Ilya Krishtal
Keyword(s):  
Krylov Subspace ◽  
Krylov Subspace Methods ◽  
Subspace Methods

Identification of Linear Tire Cornering Stiffness Using Subspace Methods

2014 ◽  
Vol 701-702 ◽  
pp. 492-497
Author(s):  
Teng Yue Ba ◽  
Xi Qiang Guan ◽  
Jian Wu Zhang
Keyword(s):  
Data Driven ◽  
Subspace Identification ◽  
Subspace Methods ◽  
Identification Methods ◽  
The Road ◽  
Strong Robustness ◽  
Subspace Algorithms ◽  
Double Lane Change ◽  
On The Road ◽  
Lane Change Test

In this paper, subspace identification methods are proposed to estimate the linear tire cornering stiffness, which are only based on the road tests data without any prior knowledge. This kind of data-driven method has strong robustness. In order to validate the feasibility and effectiveness of the algorithms, a series of standard road tests are carried out. Comparing with different subspace algorithms used in road tests, it can be concluded that the front tire cornering stiffness can be estimated accurately by the N4SID and CCA methods when the double lane change test data are taken into analysis.

POWER GRIDS ANALYSIS IN COMPRESSED KRYLOV-SUBSPACE METHODS

2008 ◽  
Vol 17 (03) ◽  
pp. 439-446
Author(s):  
HAOHANG SU ◽  
YIMEN ZHANG ◽  
YUMING ZHANG ◽  
JINCAI MAN
Keyword(s):  
Present Method ◽  
Large Scale ◽  
Krylov Subspace ◽  
Power Grid ◽  
Excellent Result ◽  
Krylov Subspace Methods ◽  
Power Grids ◽  
Improved Method ◽  
Subspace Methods ◽  
Transient Simulations

An improved method is proposed based on compressed and Krylov-subspace iterative approaches to perform efficient static and transient simulations for large-scale power grid circuits. It is implemented with CG and BiCGStab algorithms and an excellent result has been obtained. Extensive experimental results on large-scale power grid circuits show that the present method is over 200 times faster than SPICE3 and around 10–20 times faster than ICCG method in transient simulations. Furthermore, the presented algorithm saves the memory usage over 95% of SPICE3 and 75% of ICCG method, respectively while the accuracy is not compromised.

Nonstationary Consistency of Subspace Methods

2007 ◽  
Vol 52 (6) ◽  
pp. 974-984 ◽  
Author(s):  
Albert Benveniste ◽  
Laurent Mevel
Keyword(s):  
Subspace Methods
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