Different Scenarios on Denoising of Signals in the Intrinsic Mode Function Selection Framework

ABSTRACT

Without having any information of original signal, estimating the desired signal from noisy measurements is a challenging problem. In this paper, the denoising problem of signals corrupted by additive white Gaussian noise (AWGN) is considered in the empirical mode decomposition (EMD) framework, and five different noise suppression scenarios based on the various combinations of intrinsic mode functions (IMFs) that arise from applying the EMD to a given noisy signal are suggested. In these scenarios, the idea of discarding noise-dominant IMFs from a noisy signal is adopted. Considering the root-mean-square error and the signal-to-error ratio, the performance of each scenario is evaluated over simulated and real signals contaminated by AWGN with different signal-to-noise ratios (SNRs). It is observed from simulations that the proposed scenarios provide satisfactory denoising performance especially for positive SNRs and can be exploited as a primary stage in whole of the noise-diminishing applications.

KEYWORDS:

• Empirical mode decomposition
• intrinsic mode function
• mode selection
• noise reduction
• nonlinear
• non-stationary

Acknowledgments

The authors are grateful to the anonymous referees for their constructive comments and suggestions on the presentation of this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Aydin Kizilkaya

Aydin Kizilkaya was born in Augsburg, Germany, in 1972. He received the BSc degree from Karadeniz Technical University, Trabzon, Turkey, in 1994 and the MSc degree from Pamukkale University, Denizli, Turkey, in 1997, both in electrical and electronics engineering, and the PhD degree in electronics and communication engineering from Istanbul Technical University, Istanbul, Turkey, in 2006. In 1995, he joined Pamukkale University, where he is now an associate professor of communication engineering, and has been a head of communication engineering subdivision since 2009. He was a deputy head of the electrical and electronics engineering department from 2009 to 2012. His research interests include digital signal processing, multi-dimensional signal processing, and applications of signal processing.

E-mail: [email protected]

Mehmet Dogan Elbi

Mehmet Dogan ELBI was born in Denizli, Turkey, in 1988. He received the BSc degree in electrical and electronics engineering from Pamukkale University, Denizli, Turkey, in 2010. Since 2012, he is a research assistant at Pamukkale University. Since 2011, he has been an MSc student at Pamukkale University. His research interests include digital signal and image processing, VHDL parallel programming, nonlinear modeling, and machine learning.