A memristive chaotic system and its application in weak signal detection

Abstract

In this paper, a novel four-dimensional memristive chaotic system is constructed by incorporating a memristor model into a three-dimensional chaotic system. Through the analysis of the Lyapunov exponent, bifurcation diagram, and Poincaré cross-section of the system, it has been observed that the system is capable of exhibiting a stable chaotic state, as well as complex dynamic behaviors, such as attractor coexistence, transient chaos, and offset boosting. To validate the actual existence of the system, a real circuit has been built based on Multisim simulation, and the numerical simulation results, along with the actual simulation results, are in agreement, thereby confirming the practical feasibility of the circuit. To achieve weak signal detection, a backstepping synchronization controller has been designed, which can detect the frequency and amplitude of unknown signals. It is obvious that this method does not require the determination of the critical threshold. Instead of, it relies on the system being in a chaotic state. The proposed detection method provides a new perspective for weak signal detection.

The hyperbolic sine chaotification model and its applications

“…They represent a class of nonlinear systems that exhibit both order and disorder, with characteristics such as sensitivity to initial conditions, nonperiodicity, and ergodicity [2]. Due to these characteristics, chaotic systems have garnered widespread attention from researchers, and they have been applied in multiple fields, such as signal processing [3][4][5], financial markets [6][7][8], information security [9][10][11], artificial intelligence [12][13][14], data optimization [15][16][17], and cryptography [18][19][20]. In chaos-based applications, the performance of chaotic systems is crucial.…”

Dynamics of memristive Liu system and its DSP implementation

“…Despite its complexity and sensitivity to initial conditions, chaos theory has received a lot of attention recently. Active control of chaotic systems is replacing passive observation, with chaotic patterns found in a variety of disciplines including chaos control [1,2], secure communication [3], artificial intelligence [4,5], weak signal detection [6,7], econometric systems [8], and image encryption [9].…”