Optimized analog filter approximation via evolutionary algorithms

In this work, fast and efficient evolutionary algorithms, Artificial Bee Colony (ABC), Particle Swarm Optimization (PSO), Differential Evolution (DE), Harmony Search (HS) 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. Three different order of transfer functions are taken into consideration. Compared to conventional methods, all evolutionary algorithms obtain less approximation error in a short computation time.

[1]  R. Weigel,et al.  A New Approach for Analog Filter Design with Mask Constraints Utilizing Linear Programming , 2007, 2007 International Symposium on Signals, Systems and Electronics.

[2]  Zong Woo Geem,et al.  A New Heuristic Optimization Algorithm: Harmony Search , 2001, Simul..

[3]  Vlastimir D. Pavlović,et al.  New class of filter functions generated most directly by the Christoffel–Darboux formula for classical orthonormal Jacobi polynomials , 2011 .

[4]  Yichuang Sun,et al.  Continuous-Time Active Filter Design , 1998 .

[5]  Dervis Karaboga,et al.  A comparative study of Artificial Bee Colony algorithm , 2009, Appl. Math. Comput..

[6]  Maurice Clerc,et al.  The particle swarm - explosion, stability, and convergence in a multidimensional complex space , 2002, IEEE Trans. Evol. Comput..

[7]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[8]  Truong Q. Nguyen,et al.  Optimized Analog Filter Designs With Flat Responses by Semidefinite Programming , 2009, IEEE Transactions on Signal Processing.

[9]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[10]  Una-May O'Reilly,et al.  Filter approximation using explicit time and frequency domain specifications , 2006, GECCO '06.

[11]  Umut Engin Ayten,et al.  Low-pass filter approximation with evolutionary techniques , 2011, 2011 7th International Conference on Electrical and Electronics Engineering (ELECO).

[12]  T. Krink,et al.  Particle swarm optimisation with spatial particle extension , 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

[13]  R. Storn,et al.  Differential Evolution - A simple and efficient adaptive scheme for global optimization over continuous spaces , 2004 .

[14]  Leon O. Chua,et al.  Linear and nonlinear circuits , 1987 .

[15]  Brian L. Evans,et al.  An automated framework for multicriteria optimization of analog filter designs , 1999 .

[16]  Truong Q. Nguyen,et al.  Optimized Analog Flat Filter Design , 2010, IEEE Transactions on Signal Processing.

[17]  Kenneth C. Smith,et al.  Microelectronic circuits, 2nd ed. , 1987 .

[18]  Dervis Karaboga,et al.  A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm , 2007, J. Glob. Optim..

[19]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[20]  Riccardo Poli,et al.  Particle swarm optimization , 1995, Swarm Intelligence.

[21]  D. Karaboga,et al.  Artificial Bee Colony ( ABC ) , Harmony Search and Bees Algorithms on Numerical Optimization , 2009 .

[22]  R. Weigel,et al.  A Novel Method Based Upon Nonlinear Optimization for Analog Filter Design with Mask Constraints , 2007, 2007 International Symposium on Signals, Systems and Electronics.