Filtering Techniques for Chaotic Signal Processing

Butusov, Denis N.; Каримов, Тимур; Voznesenskiy, Alexander S.; Kaplun, Dmitry; Андреев, В. С.; Ostrovskii, Valerii Y.

doi:10.3390/electronics7120450

Cited by 17 publications

(11 citation statements)

References 32 publications

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“…The most widely used in ADFs are digital filters with a finite impulse response (FIR) [5]. Adaptive filtering is used in acoustic systems [6], image processing [7], equalizers designed to level the characteristics of communication channels [8], systems, using adaptive antenna arrays [9].…”

Section: Introductionmentioning

confidence: 99%

Technique to Adjust Adaptive Digital Filter Coefficients in Residue Number System Based Filters

et al. 2021

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The paper discusses adaptive filtering using Least Mean Square (LMS) and Recursive Least Square (RLS) algorithms. An algorithm for adjusting the coefficients of an adaptive digital filter in the Residue Number System and a procedure of developed algorithm applying depending on filter length and signal length are proposed. Mathematical modeling of the considered algorithms is performed. Examples are presented to demonstrate how the proposed technique can help the designer in the adjustment of the filter coefficients without the need for extensive trial-and-error procedures. The analysis of the denoising quality and computational complexity is made. Synthetic and real data (earthquake recording) were used while testing. The proposed algorithm surpasses the existing ones like LMS and RLS, and their modifications in a number of parameters: adaptation (denoising) quality, ease of implementation, execution time. The main difference between the developed algorithm is the sequential adaptation of each coefficient with zero error. In the known algorithms, the entire vector of coefficients is iteratively adapted, with some specified accuracy. The iterations (steps) number is determined by the input signal length for all algorithms.

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Section: Introductionmentioning

confidence: 99%

Technique to Adjust Adaptive Digital Filter Coefficients in Residue Number System Based Filters

et al. 2021

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“…Lai and Leng [6] considered a two-dimensional Duffing oscillator and proposed the weak-signal detection approach based on the GPASR model. A filtering technique through chaotic regime-switching is proposed by Denis et al [7]. e inherent deficiency of the measuring mechanism leads to a mass of various noises to the effective signal inevitably.…”

Section: Introductionmentioning

confidence: 99%

Detection of Weak Signal Based on Parameter Identification of Delay Differential System with Noise Disturbance

Wang

Yang

Zhang

2020

Mathematical Problems in Engineering

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Extraction of the weak signals is crucial for fault prognostics in which case features are often very weak and masked by noise. In the time domain, the detection of weak signals depends on the identification of nonlinear parameters. A new signal detection and estimation method based on the incremental harmonic balance (IHB) is developed from the stochastic Van der Pol–Duffing equation with delayed feedback under parametric excitation. This is the first time that the IHB has been applied for the identification of parameters in stochastic delay differential equations (SDDEs). Compared to the method of intermittency transition between order and chaos to detect weak signals, this new method is more direct and the calculation result is what we want to obtain. This new method is suitable for the generalization and application of SDDEs.

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“…Recently, a new filtering algorithm based on cascade of driven chaotic oscillators is proposed in [23]. That paper pointed out that chaotic system can work as filter, and proposed a non-linear filter construction as a cascade of driven Rössler oscillators.…”

Section: Introductionmentioning

confidence: 99%

Signal Denoising Based on Duffing Oscillators System

Luo¹,

Cui

2020

IEEE Access

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Signal denoising is an important aspect of signal processing. It is a meaningful direction to solve this problem by using chaotic oscillator. As a kind of chaotic oscillator, Duffing oscillator is often used in the field of periodic signal or pulse signal detection, but it has not been used in signal denoising. In this paper, a new Duffing oscillators system for signal denoising is proposed. The system utilizes the coupling between linear and nonlinear restoring forces of the oscillators to achieve complete synchronization of the system. Because the external signal will cause a large deviation of the oscillator's trajectory, while the Gauss white noise will only produce a small deviation. Based on this phenomenon, signal denoising can be realized. The simulation results show that, compared with the existing technology, our method is effective for the denoising of complex irregular signal, and can recover the mutation points of signal well. This method has less computational complexity and is easy to implement parallel computation. It can be used in real-time signal processing.

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Filtering Techniques for Chaotic Signal Processing

Cited by 17 publications

References 32 publications

Technique to Adjust Adaptive Digital Filter Coefficients in Residue Number System Based Filters

Technique to Adjust Adaptive Digital Filter Coefficients in Residue Number System Based Filters

Detection of Weak Signal Based on Parameter Identification of Delay Differential System with Noise Disturbance

Signal Denoising Based on Duffing Oscillators System

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