Blind Source Separation of Continuous-Time Chaotic Signals Based on Fast Random Search Algorithm

Abstract

Blind source separation (BSS) of continuous-time chaotic signals from a linear mixture is addressed in this brief. It is assumed that the functional forms of the generating systems of chaotic signals are known, and the parameters of the generating systems and the mixture matrix are unknown. The problem of determining the parameters and the mixture matrix is formulated as an optimization one. A fast random search (FRS) algorithm is, therefore, proposed. Experimental results demonstrate that the FRS algorithm can solve the indeterminacy problem in BSS and show the separability of mixed signals in a high noise background. Index Terms-Blind source separation (BSS), continuous-time chaotic signals, fast random search (FRS).

Extraction of Weak Harmonic Target Signal from Ionospheric Noise of High Frequency Surface Wave Radar

“…Uchida [3] used two microchip solid-state lasers with external modulation as chaotic signal sources and the simulation results showed that algorithm gived a good performance in the separation and denoising of mixed noisy signals in the presence of a white Gaussian noise or stationary colored noise, when analysis based on the second-order statistics was applicable [4]. Xie [5] studied blind source separation of continuous-time chaotic signals based on fast random search algorithm. A fast random search (FRS) algorithm was, therefore, proposed.…”

Gradient method for blind chaotic signal separation based on proliferation exponent

“…Much work has been done to separate chaotic signals by means of coupled synchronization, [4,5] particle filter, [6] or Kalman filter. [7,8] However, potential applications of these methodologies are confined to some scenarios where the equations of the chaotic maps are known by transcendental knowledge.…”

Homotopy-Inspired Grenade Explosion Algorithm for Global Numerical Optimization

“…Grenade explosion algorithm(GEA), which was proposed by Ali Ahrari and Ali A. Atai in 2010 [1], is a population-based heuristics optimization technique inspired from the observation of a grenade explosion. Though GEA has many advantages, it may easily get trapped in a local optimum when solving complex optimization problems.Several studies have shown that incorporating some other optimization algorithms can greatly improve the search capability of Grenade explosion algorithm(GEA) [2,3]. In order to improve GEA's performance on complex optimization problems, we present the homotopy-inspired Grenade explosion algorithm(GEA) utilizing a new continuous transformation strategy from an easy problem to the given problem.…”