Average wavelet coefficient-based detection of chaos in oscillatory circuits. Issue 1 (3rd January 2017) - Rubežić, Vesna; Djurović, Igor; Sejdić, Ervin
Abstract : Purpose: The purpose of this paper is to propose a new algorithm for detection of chaos in oscillatory circuits. The algorithm is based on the wavelet transform. Design/methodology/approach: The proposed detection is developed by using a specific measure obtained by averaging wavelet coefficients. This measure exhibits various values for chaotic and periodic states. Findings: The proposed algorithm is applied to signals from autonomous systems such as the Chua's oscillatory circuit, the Lorenz chaotic system and non-autonomous systems such as the Duffing oscillator. In addition, the detection is applied to sequences obtained from the logistic map. The results are compared to those obtained with a detrended fluctuation analysis and a time-frequency signal analysis based on detectors of chaotic states. Originality/value: In this paper, a new algorithm is proposed for the detection of chaos from a single time series. The proposed technique is robust to the noise influence, having smaller calculation complexity with respect to the state-of-the-art techniques. It is suitable for real-time detection with delay that is about half of the window width.