A proof of convergence for Ant algorithms
Information Sciences—Informatics and Computer Science: An International Journal
Exchange strategies for multiple Ant Colony System
Information Sciences: an International Journal
A particle swarm optimization approach to nonlinear rational filter modeling
Expert Systems with Applications: An International Journal
Information Sciences: an International Journal
GSA: A Gravitational Search Algorithm
Information Sciences: an International Journal
Digital secure communication via chaotic systems
Digital Signal Processing
Design and implementation of digital secure communication based on synchronized chaotic systems
Digital Signal Processing
A hybrid genetic algorithm with the Baldwin effect
Information Sciences: an International Journal
A study of particle swarm optimization particle trajectories
Information Sciences: an International Journal
Filter modeling using gravitational search algorithm
Engineering Applications of Artificial Intelligence
Ant colony optimisation to identify genetic variant association with type 2 diabetes
Information Sciences: an International Journal
Information Sciences: an International Journal
Rosenbrock artificial bee colony algorithm for accurate global optimization of numerical functions
Information Sciences: an International Journal
Information Sciences: an International Journal
Cellular particle swarm optimization
Information Sciences: an International Journal
Self-adaptive learning based particle swarm optimization
Information Sciences: an International Journal
An optimal image watermarking approach based on a multi-objective genetic algorithm
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Information Sciences: an International Journal
Ant system: optimization by a colony of cooperating agents
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Engineering Applications of Artificial Intelligence
A discrete gravitational search algorithm for solving combinatorial optimization problems
Information Sciences: an International Journal
Hi-index | 0.07 |
Research in recent years has seen the development of chaotic systems for secure communication. However, most chaotic systems fail to compensate for channel noise which often degrades the performance of chaos-based secure communication systems. In this work, we propose a chaotic secure communication scheme based on the Modified Gravitational Search Algorithm (MGSA), which minimizes premature convergence of Gravitational Search Algorithm (GSA). Here, we apply the MGSA-based filter to the proposed communication scheme to reduce channel noise. Computer simulations with the unified chaotic map are done to verify the feasibility of the proposed secure communication scheme. The results show that the proposed new scheme accurately estimates the states and information symbols, and provides a lower bit error rate (BER) than existing secure communication schemes. Furthermore, the MGSA is tested on the nonlinear filter modeling and compared with GSA and particle swarm optimization (PSO). The results confirm the high performance of the MGSA-based filter in parameters estimation of nonlinear filter modeling. In other words, the more accurately the MGSA estimates the parameters, the more noise the filter reduces.