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Particle swarm optimization (PSO) is a stochastic optimization algorithm which usually suffers from local confinement losing its diversity. In this paper, we have proposed an efficient coordinator guided PSO (ECG-PSO), which provides a good diversity to the swarms maintaining good convergence speed and hence improves the fitness and robustness of the technique. We comprehensively evaluate the performance...
In cognitive radio technology, constant changes in the environment like change in background noise, movements of the users or transmitters, interferences, etc. require the spectrum sensing parameters like detection threshold to be changed. Else, errors in spectrum sensing arises which either causes interference between transmission from primary and secondary users, or the secondary user misses an...
This paper presents a deterministic model of Ant System and its subsequent frequency domain analysis. Classical Ant System is modeled as a first order and first degree differential equation form without violating the stochastic nature of the ant dynamics. Then, a transfer function model is developed and the system characterization is done in frequency domain. It is helpful to explore the system behavior...
Spectrum sensing is an important aspect for Cognitive Radio Networks (CRNs) to enable efficient usage of the licensed spectrum bands when the primary users are inactive. For real time application, rapid detection of spectrum holes are of prime importance. In this paper, Finite State Machine (FSM) based SoC architecture design for energy based single and cooperative spectrum sensing techniques have...
In this paper, we propose a modified model of pheromone updation for Ant-System (AS), entitled as Improved Ant System (IAS), and develop a new modeling framework for the above mentioned AS using the properties of basic Adaptive Filters. Here, we have exploited the properties of Least Mean Square (LMS) algorithm for the pheromone updation to find out the best minimum tour length for the Travelling...
Time Adaptive Ant System (TAAS) is the new proposed algorithm with modified pheromone updation rule. Here, we have exploited the properties of Time adaptive Least Mean Square (LMS) algorithm for the pheromone updation rule to resolve the basic shortcoming of easily falling into local optima and slow convergence speed. The improved algorithm has better global search ability and good convergence speed...
In this paper, we have proposed a modified model of dynamic pheromone updation for ant system, entitled as Dynamic Adaptive Ant System (DAAS) by incorporating the dynamic property in the pheromone trail factor with the help of Least Means Square (LMS) algorithm. Here, static pheromone trail factor, ρ, in ant learning equation, has been made dynamic and adaptive to increase the effectiveness of the...
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