There are two types of digital filters including Infinite Impulse Response (IIR) and Finite Impulse Response (FIR). IIR filters attract more attention as they can decrease the filter order significantly compared to FIR filters. Owing to multi-modal error surface, simple powerful optimization techniques should be utilized in designing IIR digital filters to avoid local minimum. Imperialist compe...

Design a new novel intelligence algorithm which is called as chaotic quantum bee colony optimization (CQBCO) for discrete optimization problem. The proposed CQBCO applies the chaotic theory to quantum bee colony optimization (QBCO), which is an effective discrete optimization algorithm. Then the proposed chaotic quantum bee colony algorithm is used to solve benchmark functions and optimization ...

Particle swarm optimization algorithm in solving complex functions, such as slow convergence, accuracy is not high, easily falling into local optimum problem. Based on the chaos optimization is introduced into particle swarm optimization algorithm, given the chaotic particle swarm optimization algorithm. In order to improve the image quality of CMOS image sensor, the image of the main noise sou...

The nonlinear behavior analysis and chaos control for Duffing-Holmes chaotic system is discussed in the paper. In order to suppress the irregular chaotic motion, an optimal backstepping controller is designed. The backstepping method consists of parameters with positive values. The improper selection of the parameters leads to inappropriate responses or even may lead to instability of the syste...

The chaotic simulated annealing algorithm for combinatorial optimization problems is examined in the light of the global bifurcation structure of the chaotic neural networks. We show that the result of the chaotic simulated annealing algorithm is primarily dependent upon the global bifurcation structure of the chaotic neural networks and unlike the stochastic simulated annealing infinitely slow...

Differential evolution algorithm combined with chaotic pattern search(DE-CPS) for global optimization is introduced to improve the performance of simple DE algorithm. Pattern search algorithm using chaotic variables instead of random variables is used to accelerate the convergence of solving the objective value. Experiments on 6 benchmark problems, including morbid Rosenbrock function, show tha...

Clustering is a popular data analysis and data mining technique. In this paper, a novel chaotic particle swarm fuzzy clustering (CPSFC) algorithm based on chaotic particle swarm (CPSO) and gradient method is proposed. Fuzzy clustering model optimization is challenging, in order to solve this problem, adaptive inertia weight factor (AIWF) and iterative chaotic map with infinite collapses (ICMIC)...