Details

Title

Application of evolutionary algorithm to design minimal phase digital filters with non-standard amplitude characteristics and finite bit word length

Journal title

Bulletin of the Polish Academy of Sciences: Technical Sciences

Yearbook

2011

Numer

No 2 June

Publication authors

Divisions of PAS

Nauki Techniczne

Publisher

Polish Academy of Sciences

Date

2011

Identifier

ISSN 0239-7528, eISSN 2300-1917

References

Lyons R. (2000), Introduction to Digital Signal Processing. ; Slowik A. (2004), Evolutionary design of IIR digital filters with non-standard amplitude characteristics, Proc. 3-rd Nat. Conf. Electronics, 1, 345. ; Erba M. (2001), Digital filter design through simulated evolution, Proc. ECCTD '01, 2, 137. ; Rainer S. (1997), Differential evolution — a simple and efficient heuristic for global optimization over continuous spaces, J. Global Optimization, 11, 341, doi.org/10.1023/A:1008202821328 ; Price K. (1999), New Ideas in Optimization, 79. ; Kennedy J. (2001), Swarm Intelligence. ; Pham D. (2006), The bees algorithm - a novel tool for complex optimisation problems, IPROMS 2006, Intelligent Production, Machines and Systems, 1. ; Slowik A. (2008), Design and optimization of IIR digital filters with non-standard characteristics using continous ant colony optimization algorithm, 5th Hellenic Conf. on Artificial Intelligence, Lecture Notes in Computer Science, 5138, 395. ; Socha K. (2008), Ant colony optimization for continous domains, Eur. J. Operational Research, 185, 3, 1155, doi.org/10.1016/j.ejor.2006.06.046 ; Dorigo M. (1996), Ant system: optimization by a colony of cooperating agents, IEEE Transactions on SMC-B, 26, 1, 29. ; Beyer H. (2002), Evolution strategies: a comprehensive introduction, J. Natural Computing, 1, 1, 3, doi.org/10.1023/A:1015059928466 ; Becerra R. (2006), Cultured differential evolution for constrained optimization, Computer Methods in Applied Mechanics and Engineering, 195, 33-36, 4303, doi.org/10.1016/j.cma.2005.09.006 ; Goldberg D. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning. ; Michalewicz Z. (1992), Genetic Algorithms + Data Structures = Evolution Programs, doi.org/10.1007/978-3-662-02830-8 ; Arabas J. (2001), Lectures on Evolutionary Algorithms. ; Benvenuto N. (1989), Finite wordlength digital filter design using an annealing algorithm, Int. Conf. on Acoustics, Speech, and Signal Processing, 2, 861, doi.org/10.1109/ICASSP.1989.266564 ; Nakamoto M. (2007), Finite wordlength design for IIR digital filters based on the modified least-square criterion in the frequency domain, null, 462. ; Karaboga N. (2003), Performance comparison of genetic algorithm based design methods of digital filters with optimal magnitude response and minimum phase, null, 1. ; Venkata N. (1999), Optimal design of real and complex minimum phase digital FIR filters, null, 1. ; Orfanidis S. (1995), Introduction to Signal Processing. ; Ding H. (2004), Anadaptive speech enhancement method for siren noise cancellation, Applied Acoustics, 65, 385, doi.org/10.1016/j.apacoust.2003.10.006 ; <i>TMS320C54x DSP Library Programmer's Reference</i>, Texas Instruments, Dallas, 2001. ; <i>TMS320C55x DSP Library Programmer's Reference</i>, Texas Instruments, Dallas, 2002. ; Gan W. (2006), Teaching DSP software development: from design to fixed-point implementations, IEEE Trans. on Education, 49, 1, 122, doi.org/10.1109/TE.2005.863425 ; Baicher G. (2006), Optimization of finite word length coefficient IIR digital filters through genetic algorithms - a comparative study, Lecture Notes on Computer Science, 4222, 641, doi.org/10.1007/11881223_79 ; Karaboga N. (2004), Design of minimum phase digital IIR filters by using genetic algorithm, null, 1. ; Slowik A. (2010), Evolutionary design of digital filters with nonstandard amplitude characteristics and finite bit word length, Proc. IX Nat. Conf. on Electronics, 1, 255.

DOI

10.2478/v10175-011-0016-z

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