Abstract
In this work, two evolutionary techniques, Particle Swarm Optimization (PSO) and Artificial Bee Colony (ABC) algorithms are used to optimize the denominator coefficients of the low-pass filter transfer function. Optimum selection of the coefficients will approximate the transfer function to ideal characteristic. Two different order of transfer functions are taken into consideration. Compared to conventional methods, both PSO and ABC minimize the approximation error in a short computation time.
Keywords
Particle swarm optimization
Transfer function
Evolutionary computation
Mathematical optimization
Filter (signal processing)
Computation
Selection (genetic algorithm)
Evolutionary algorithm
Approximation error
Computer science
Ideal (ethics)
Mathematics
Algorithm
Applied mathematics
Artificial intelligence
Engineering
Subject Areas
Metaheuristic Optimization Algorithms Research
·Artificial Intelligence ·Physical Sciences
Advanced Fiber Optic Sensors
·Electrical and Electronic Engineering ·Physical Sciences
Advanced Adaptive Filtering Techniques
·Computational Mechanics ·Physical Sciences
Citations by Year
2012: 1
2013: 1
2014: 2
2019: 1
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