Digital filter design
Discrete-time signal processing (2nd ed.)
Discrete-time signal processing (2nd ed.)
Design of arbitrary FIR log filters by genetic algorithm approach
Signal Processing
FIR Digital Filters Design Based on Quantum-behaved Particle Swarm Optimization
ICICIC '06 Proceedings of the First International Conference on Innovative Computing, Information and Control - Volume 1
Linear phase FIR filter design using particle swarm optimization and genetic algorithms
Digital Signal Processing
The Design of IIR Digital Filter Based on Chaos Particle Swarm Optimization Algorithm
WGEC '08 Proceedings of the 2008 Second International Conference on Genetic and Evolutionary Computing
An Adaptive Inertia Weight Particle Swarm Optimization Algorithm for IIR Digital Filter
AICI '09 Proceedings of the 2009 International Conference on Artificial Intelligence and Computational Intelligence - Volume 01
Differential Cultural Algorithm for Digital Filters Design
ICCMS '10 Proceedings of the 2010 Second International Conference on Computer Modeling and Simulation - Volume 03
Satisfactory Design of IIR Digital Filter Based on Chaotic Mutation Particle Swarm Optimization
WGEC '09 Proceedings of the 2009 Third International Conference on Genetic and Evolutionary Computing
Particle swarm optimization with quantum infusion for system identification
Engineering Applications of Artificial Intelligence
Firefly algorithms for multimodal optimization
SAGA'09 Proceedings of the 5th international conference on Stochastic algorithms: foundations and applications
Filter modeling using gravitational search algorithm
Engineering Applications of Artificial Intelligence
DEPSO and PSO-QI in digital filter design
Expert Systems with Applications: An International Journal
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Optimal digital filter design in digital signal processing has thrown a growing influence on communication systems. FIR filter design involves multi-parameter optimization, on which the existing optimization algorithms do not work efficiently. For which different optimization techniques can be utilized to determine the impulse response coefficient of a filter and try to meet the ideal frequency response characteristics. In this paper, FIR low pass, high pass, band pass and band stop filters have been designed using a new meta-heuristic search method, called firefly algorithm. Firefly Algorithm is inspired by the flash pattern and characteristics of fireflies. The performance of the designed filters has been compared with that obtained by real coded genetic algorithm RGA, standard PSO and differential evolution DE optimization techniques. Differential evolution DE is already one of the most powerful stochastic real-parameter optimization algorithms in current use. Here the firefly algorithm FA technique has proven a significant advantage. For the problem at hand, the simulation of designing FIR filters has been done and the simulation results demonstrate that Firefly algorithm is better than other relevant algorithms, not only in the convergence speed but also in the performance of the designed filter.