Abstract
In this document, we are studying a technique of time-frequency analysis called Synchrosqueezing Stockwell Transform (SSST) to satisfy the processing and interpretation of high resolution signals. The SSST technique squeezes and reconstructs the outcomes of complicated spectra coefficients along the direction of frequency. In order to concentrate the energy distribution on the time-frequency spectrum throughout the actual instantaneous frequency of the signal, and to improve the corresponding time-frequency resolution is the aim. The experimental results performed on chirp signals depict that the proposed method can correctly give a better energy concentration around the instantaneous frequency with less smearing of energy.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Boashash, B.: Estimating and interpreting the instantaneous frequency of a signal Algorithms and applications. Proc. IEEE 80(4), 540–568 (1992)
Daubechies, I., Jianfeng, L., HT, W.: Synchrosqueezed wavelet transforms: an empirical mode decomposition-like tool. Appl. Comput. Harmon. Anal. 30(2), 243–261 (2011)
Herrera, R.H., Han, J., van der Baan, M.: Applications of the synchrosqueezing transform in seismic time-frequency analysis. Geophysics 79(3) (2014)
Huang, Z., et al.: Synchrosqueezing S-transform and its application in seismic spectral decomposition. IEEE Trans. Geosci. Remote Sens. 54(2), 817–825 (2016)
Jabloun, M., et al.: Estimation of the instantaneous amplitude and frequency of non-stationary short-time signals. Sig. Process. 88(7), 1636–1655 (2008)
Daubechies, I., Wang, Y.G., Wu, H.T.: ConceFT: concentration of frequency and time via a multitapered synchrosqueezed transform. Phil. Trans. R. Soc. A (2016)
Li, C., Liang, M.: A generalized synchrosqueezing transform for enhancing signal time–frequency representation. Sig. Process. 92(9), 2264–2274 (2012)
Auger, F., et al.: Time-frequency reassignment and synchrosqueezing: an overview. IEEE Signal Process. Mag. 30(6), 32–41 (2013)
Daubechies, I., Lu, J., Wu, H.T.: Synchrosqueezed wavelet transforms: An empirical mode decomposition-like tool. Appl. Comput. Harmon. Anal. 30(2), 243–261 (2011)
Stockwell, R.G., Mansinha, L., Lowe, P.R.: Localization of the complex spectrum: the S transform. IEEE Trans. Signal Process. 44(4), 998–1001 (1996)
Stockwell, R.G., Mansinha, L., Lowe, R.P.: Localization of the complex spectrum: the S transform. IEEE Trans. Signal Process. 44(4), 998–1001 (1996)
Picinbono, B.: Instantaneous frequency of a signal, time-frequency analysis: concepts and methods 37–60
Picinbono, B.: On instantaneous amplitude and phase of signals. IEEE Trans. Signal Process. 45(3), 552–560 (1997)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Sahoo, S., Priyadarshini, S.B.B., Bagjadab, A.B., Majhi, S.K. (2021). Energy Efficient Chrip Signal Using Stockwell Transform. In: Mishra, D., Buyya, R., Mohapatra, P., Patnaik, S. (eds) Intelligent and Cloud Computing. Smart Innovation, Systems and Technologies, vol 194. Springer, Singapore. https://doi.org/10.1007/978-981-15-5971-6_56
Download citation
DOI: https://doi.org/10.1007/978-981-15-5971-6_56
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-5970-9
Online ISBN: 978-981-15-5971-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)