Computation- and Space-Efficient Implementation of SSA

@article{Korobeynikov2009ComputationAS,
  title={Computation- and Space-Efficient Implementation of SSA},
  author={A. Korobeynikov},
  journal={ArXiv},
  year={2009},
  volume={abs/0911.4498}
}
The computational complexity of different steps of the basic SSA is discussed. It is shown that the use of the general-purpose "blackbox" routines (e.g. found in packages like LAPACK) leads to huge waste of time resources since the special Hankel structure of the trajectory matrix is not taken into account. We outline several state-of-the-art algorithms (for example, Lanczos-based truncated SVD) which can be modified to exploit the structure of the trajectory matrix. The key components here are… Expand
72 Citations
Estimation of Signal Parameters Using SSA and Unitary Root-Music
  • V. Vasylyshyn
  • Computer Science
  • 2019 IEEE International Scientific-Practical Conference Problems of Infocommunications, Science and Technology (PIC S&T)
  • 2019
Fast ESPRIT algorithms based on partial singular value decompositions
On the choice of parameters in Singular Spectrum Analysis and related subspace-based methods
Semi-nonparametric singular spectrum analysis with projection
K-SVD Meets Transform Learning: Transform K-SVD
...
1
2
3
4
5
...

References

SHOWING 1-10 OF 36 REFERENCES
The Lanczos algorithm with partial reorthogonalization
2D-extension of Singular Spectrum Analysis: algorithm and elements of theory
The Design and Implementation of FFTW3
Adaptive Projection Subspace Dimension for the Thick-Restart Lanczos Method
Perturbation Analysis of Subspace-Based Methods in Estimating a Damped Complex Exponential
Calculating the singular values and pseudo-inverse of a matrix
  • G. Golub, W. Kahan
  • Mathematics, Computer Science
  • Milestones in Matrix Computation
  • 2007
On the choice of parameters in Singular Spectrum Analysis and related subspace-based methods
FFT-based preconditioners for Toeplitz-block least squares problems
...
1
2
3
4
...