Parametric and Non-Parametric Spectral Signal Processing Techniques for Estimation of Periodicity in Sunspot Numbers

Spectral signal processing techniques for estimation of preiodcity in sun spot numbers

Authors

  • Waseem Iqbal School of Engineering, Department of Electrical Engineering, University of Management & Technology, Lahore, Pakistan
  • Muhammad Shoaib School of Engineering, Department of Electrical Engineering, University of Management & Technology, Lahore, Pakistan
  • Jameel Ahmad School of Engineering, Department of Electrical Engineering, University of Management & Technology, Lahore, Pakistan
  • Muhammad Asim Butt School of Engineering, Department of Electrical Engineering, University of Management & Technology, Lahore, Pakistan
  • Abdullah Khalid School of Engineering, Department of Electrical Engineering, University of Management & Technology, Lahore, Pakistan
  • Muhammad Adnan School of Engineering, Department of Electrical Engineering, University of Management & Technology, Lahore, Pakistan

Keywords:

Sunspot, Periodogram, Solar Activity, Blackman-Tuckey, Yule-Walker Method, Parametric and Non- Parametric Spectral Estimation

Abstract

Sunspots occur due to magnetic disturbances on the surface of the sun. The sunspot activity effects weather on earth and also affect the earth temperature. In this research paper, various spectral estimation techniques for estimation of universal cyclic behavior of sunspot numbers are discussed. Spectral analysis has been based on two different approaches, namely parametric and non-parametric estimation. The performance of various parametric and non-parametric spectral estimation methods has been compared and frequency of occurrence of sunspots is calculated. MATLAB computer simulations have been extensively used for various estimator settings to arrive at correct results. The results show that the parametric spectral estimation techniques show better and consistent performance as compared to non-parametric spectral estimation techniques.

References

Schwabe, S. H. Solar observations during 1843. In: Astronomische Nachrichten, 20(495): 234–235 (1843).

Schuster, A. On the Periodicities of Sun spots. Philosophical Transactions of the Royal Society. 206: 69–100 (1906).

Yule, G.U. On a Method of Investigating Periodicities in Disturbed Series, with Special Reference to Wolfer’s Sunspot Numbers. Philosophical Transactions of the Royal Society.226: 267–298 (1927).

Le, G. M. & J. L. Wang. Wavelet Analysis of Several Important Periodic Properties in the Relative Sunspot Numbers. Chinese Journal of Astronomy and Astrophysics. 3: 391–394 (2003).

Hayes, M. H. Statistical Digital Signal Processing and Modeling. John Wiley and Sons, Inc, (1996).

Samin, R.E., M.S. Saealal., A. Khamis., S. Isa.,R.M. Kasmani. Forecasting sunspot numbers with Feedforward Neural Networks (FNN) using ‘Sunspot Neural Forecaster’ system. 2011 International Conference on Electrical, Control and Computer Engineering (INECCE). 1-5 (2011).

Guan, X., L. Sun., F. Yu & X. Li. Sunspot number time series prediction using neural networks with quantum gate nodes. 2014 11th World Congress on Intelligent Control and Automation (WCICA). 4647- 4650 (2014).

Malik, R.A., M. Abdullah., S. Abdullah., M.J. Homam. The influence of sunspot number on high frequency radio propagation. 2014 IEEE Asia- Pacific Conference on Applied Electromagnetics (APACE). 107-110 (2014).

http://www.ngdc.noaa.gov/stp/SOLAR [accessed on July 1, 2017]

Stoica, P. & R.L. Moses. Spectral Analysis of Signals. Prentice Hall, 1st edition, (2005).

Shon, S. & K. Mehrotra. Performance comparison of autoregressive estimation methods. IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP ‘84). 9: 581–584 (1984).

Mitra, S.K. Digital Signal Processing: A Computer-Based Approach. McGraw-Hill Science/Engg. /Math, 2nd edition (2001).

Manolakis, D.G., V.K. Ingle & S.M. Kogan. Statistical and Adaptive Signal Processing. Artech House (2005).

Bounar, K. H., E.W. Cliver., & V. Boriakoff. A prediction of the peak sunspot number for solar cycle 23. Solar Physics. 176: 211 (1997).

Cliver, E.W., V. Boriakoff., & K.H. Bounar. The 22-year cycle of geomagnetic and solar wind activity. Journal of Geophysical Research, DOI:10.1029/96JA02037 (1996).

Du, Z. L. & H. N. Wang. The relationships of solar flares with both sunspot and geomagnetic activity. Research in Astronomy and Astrophysics. 12(4): (2012).

Liu, G. Using entropy to improve the resolution in non-parametric spectral estimation. Electronic Theses, Treatises and Dissertations. Paper. 7472:(2013).

Downloads

Published

2021-03-31

How to Cite

Iqbal, W., Shoaib, M. ., Ahmad, J. ., Butt, M. A. ., Khalid, A. ., & Adnan, M. (2021). Parametric and Non-Parametric Spectral Signal Processing Techniques for Estimation of Periodicity in Sunspot Numbers: Spectral signal processing techniques for estimation of preiodcity in sun spot numbers. Proceedings of the Pakistan Academy of Sciences: A. Physical and Computational Sciences, 56(1), 9–20. Retrieved from https://ppaspk.org/index.php/PPAS-A/article/view/146

Issue

Section

Articles