Filtering Techniques for Chaotic Signal Processing

• Main Authors: Denis Butusov, Timur Karimov, Alexander Voznesenskiy, Dmitry Kaplun, Valery Andreev, Valerii Ostrovskii
• Format: Article
• Language: English
• Published: MDPI AG 2018-12-01
• Series: Electronics
• Subjects: chaos; communication systems; chaotic synchronization; denoising; secure communications; digital signal processing; filtering; empirical modes decomposition
• Online Access: https://www.mdpi.com/2079-9292/7/12/450

The vulnerability of chaotic communication systems to noise in transmission channel is a serious obstacle for practical applications. Traditional signal processing techniques provide only limited possibilities for efficient filtering broadband chaotic signals. In this paper, we provide a comparative study of several denoising and filtering approaches: a recursive IIR filter, a median filter, a wavelet-based denoising method, a method based on empirical modes decomposition, and, finally, propose the new filtering algorithm based on the cascade of driven chaotic oscillators. Experimental results show that all the considered methods make it possible to increase the permissible signal-to-noise ratio to provide the possibility of message recognition, while the new proposed method showed the best performance and reliability.