- About this Journal ·
- Abstracting and Indexing ·
- Advance Access ·
- Aims and Scope ·
- Article Processing Charges ·
- Articles in Press ·
- Author Guidelines ·
- Bibliographic Information ·
- Citations to this Journal ·
- Contact Information ·
- Editorial Board ·
- Editorial Workflow ·
- Free eTOC Alerts ·
- Publication Ethics ·
- Reviewers Acknowledgment ·
- Submit a Manuscript ·
- Subscription Information ·
- Table of Contents
ISRN Signal Processing
Volume 2012 (2012), Article ID 643563, 10 pages
Observability of Spectral Components beyond Nyquist Limit in Nonuniformly Sampled Signals
Institute of Electronics and Photonics, Slovak University of Technology in Bratislava, Ilkovičova 3, 81219 Bratislava, Slovakia
Received 27 March 2012; Accepted 3 May 2012
Academic Editors: A. M. Peinado and G. A. Tsihrintzis
Copyright © 2012 Jozef Púčik et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
- P. Babu and P. Stoica, “Spectral analysis of nonuniformly sampled data—a review,” Digital Signal Processing, vol. 20, no. 2, pp. 359–378, 2010.
- N. R. Lomb, “Least-squares frequency analysis of unequally spaced data,” Astrophysics and Space Science, vol. 39, no. 2, pp. 447–462, 1976.
- P. Stoica, J. Li, and H. He, “Spectral analysis of nonuniformly sampled data: a new approach versus the periodogram,” IEEE Transactions on Signal Processing, vol. 57, no. 3, pp. 843–858, 2009.
- J. D. Scargle, “Studies in astronomical time series analysis. II—statistical aspects of spectral analysis of unevenly spaced data,” Astrophysical Journal, vol. 263, pp. 835–853, 1982.
- P. Vaníček, “Approximate spectral analysis by least-squares fit-Successive spectral analysis,” Astrophysics and Space Science, vol. 4, no. 4, pp. 387–391, 1969.
- P. Laguna, G. B. Moody, and R. G. Mark, “Power spectral density of unevenly sampled data by least-square analysis: performance and application to heart rate signals,” IEEE Transactions on Biomedical Engineering, vol. 45, no. 6, pp. 698–715, 1998.
- “Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology,” Circulation, vol. 93, no. 5, pp. 1043–1065, 1996.
- G. G. Berntson, J. T. Bigger, D. L. Eckberg et al., “Heart rate variability: origins, methods, and interpretive caveats,” Psychophysiology, vol. 34, no. 6, pp. 623–648, 1997.
- M. Teplan, L. Molčan, and M. Zeman, “Spectral analysis of cardiovascular parameters of rats under irregular light-dark regime,” in Proceedings of the 8th International Conference on Measurement, pp. 343–346, Smolenice, Slovak Republic, 2011.
- V. V. Vityazev, “Time series analysis of unequally spaced data: intercomparison between estimators of the power spectrum,” in Proceedings of the Astronomical Data Analysis Software and Systems VI ASP Conference Series, vol. 125, pp. 166–169, 1997.
- A. Schwarzenberg-Czerny, “The distribution of empirical periodograms: Lomb-Scargle and PDM spectra,” Monthly Notices of the Royal Astronomical Society, vol. 301, no. 3, pp. 831–840, 1998.
- J. Mateo and P. Laguna, “Improved heart rate variability signal analysis from the beat occurrence times according to the IPFM model,” IEEE Transactions on Biomedical Engineering, vol. 47, no. 8, pp. 985–996, 2000.
- M. Brennan, M. Palaniswami, and P. Kamen, “Distortion properties of the interval spectrum of IPFM generated heartbeats for heart rate variability analysis,” IEEE Transactions on Biomedical Engineering, vol. 48, no. 11, pp. 1251–1264, 2001.
- J. Púčik, O. Ondráček, E. Cocherová, and A. Sultan, “Spectrum of counts computation for HRV analysis,” in Proceedings of 19th International Conference Radioelektronika (RADIOELEKTRONIKA '09), pp. 255–258, April 2009.
- E. J. Bayly, “Spectral analysis of pulse frequency modulation in the nervous systems,” IEEE Transactions on Biomedical Engineering, vol. 15, no. 4, pp. 257–265, 1968.
- G. Moody, R. Mark, A. Zoccola, and S. Mantero, “Derivation of respiratory signals from multi-lead ECGs,” IEEE Computer Society, vol. 12, pp. 113–116, 1985.
- G. D. Clifford, F. Azuaje, P. E. McSharry, et al., Advanced Methods and Tools for ECG Data Analysis, Artech House, 2006.
- D. Widjaja, J. Taelman, S. Vandeput et al., “ECG-derived respiration: comparison and new measures for respiratory variability,” in Proceedings of the Computing in Cardiology (CinC '10), pp. 149–152, September 2010.
- A. Gersten, O. Gersten, A. Ronen, and Y. Cassuto, “The RR interval spectrum, the ECG signal and aliasing,” . Eprint, http://arxiv.org/abs/physics/9911017v1.
- J. Šurda, S. Lovás, J. Púčik, and M. Jus, “Spectral properties of ECG signal,” in Proceedings of the of the 17th International Conference Radioelektronika, pp. 537–541, Brno, Czech Republic, 2007.
- E. Toledo, I. Pinhas, D. Aravot, and S. Akselrod, “Very high frequency oscillations in the heart rate and blood pressure of heart transplant patients,” Medical and Biological Engineering and Computing, vol. 41, no. 4, pp. 432–438, 2003.
- H. A. Campbell, J. Z. Klepacki, and S. Egginton, “A new method in applying power spectral statistics to examine cardio-respiratory interactions in fish,” Journal of Theoretical Biology, vol. 241, no. 2, pp. 410–419, 2006.
- J. Púčik, M. Uhrík, A. Sultan, and A. Šurda, “Experimental setup for cardio-respiratory interaction study,” in Proceedings of the 8th Czech-Slovak Conference, Trends in Biomedical Engineering, pp. 126–129, Bratislava, Slovakia, 2009.
- R. Berger, S. Akselrod, D. Gordon, and R. Cohen, “An efficient algorithm for spectral analysis of heart rate variability,” IEEE Transactions on Bio-Medical Engineering, vol. 33, no. 9, pp. 900–904, 1986.
- W. H. Press, B. P. Flannery, S. A. Teukolsky, W. T. Vetterling, et al., Numerical Recipes in Fortran 77: The Art of Scientific Computing, vol. 1, Cambridge University Press, 1992.
- G. L. Bretthorst, “Nonuniform sampling: bandwidth and aliasing,” Concepts in Magnetic Resonance A, vol. 32, no. 6, pp. 417–435, 2008.