Perturbation expansions of signal subspaces for long signals

@article{Nekrutkin2010PerturbationEO,
  title={Perturbation expansions of signal subspaces for long signals},
  author={V. Nekrutkin},
  journal={arXiv: Numerical Analysis},
  year={2010}
}
  • V. Nekrutkin
  • Published 2010
  • Mathematics
  • arXiv: Numerical Analysis
Singular Spectrum Analysis and many other subspace-based methods of signal processing are implicitly relying on the assumption of close proximity of unperturbed and perturbed signal subspaces extracted by the Singular Value Decomposition of special "signal" and "perturbed signal" matrices. In this paper, the analysis of the main principal angle between these subspaces is performed in terms of the perturbation expansions of the corresponding orthogonal projectors. Applicable upper bounds are… Expand
18 Citations

Tables from this paper

On the choice of parameters in Singular Spectrum Analysis and related subspace-based methods
  • 106
  • PDF
Two asymptotic approaches for the exponential signal and harmonic noise in Singular Spectrum Analysis
  • 1
  • PDF
Singular Spectrum Analysis for time series: Introduction to this special issue
  • 34
  • PDF
Singular spectrum analysis based on the perturbation theory
  • 28
  • PDF
The Sliding Singular Spectrum Analysis: A Data-Driven Nonstationary Signal Decomposition Tool
  • 44
  • PDF
Remark on the norm of random Hankel matrices
  • 2
Singular Spectrum Analysis for Time Series
  • A. Zhigljavsky
  • Mathematics, Computer Science
  • International Encyclopedia of Statistical Science
  • 2011
  • 395
  • PDF
...
1
2
...

References

SHOWING 1-10 OF 36 REFERENCES
On the choice of parameters in Singular Spectrum Analysis and related subspace-based methods
  • 106
  • PDF
Singular-spectrum analysis: a toolkit for short, noisy chaotic signals
  • 1,185
Data-adaptive principal component signal processing
  • R. Kumaresan, D. Tufts
  • Mathematics
  • 1980 19th IEEE Conference on Decision and Control including the Symposium on Adaptive Processes
  • 1980
  • 48
Performance of ESPRIT for Estimating Mixtures of Complex Exponentials Modulated by Polynomials
  • 42
  • PDF
ESPRIT-estimation of signal parameters via rotational invariance techniques
  • R. Roy, T. Kailath
  • Mathematics, Computer Science
  • IEEE Trans. Acoust. Speech Signal Process.
  • 1989
  • 5,322
  • PDF
A Few Remarks on the Operator Norm of Random Toeplitz Matrices
  • 25
  • Highly Influential
  • PDF
Multiple emitter location and signal Parameter estimation
  • 10,835
  • PDF
Estimating the Angles of Arrival of Multiple Plane Waves
  • 811
Digital spectral analysis: with applications
  • 2,362
On the spectral norm of a random Toeplitz matrix
  • 47
  • PDF
...
1
2
3
4
...