Custom Winding Ratio Analysis of Evolutionary Optimized Audio Transformer

  • Martin PospisilikEmail author
  • Lukas Kouril
  • Milan Adamek
  • Ivan Zelinka
  • Roman Jasek
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 192)


This paper is intended to present a trend analysis resulting from different secondary to primary windings ratio of evolutionary optimized audio transformer. Evolutionary optimization of audio transformers is a perspective approach to the wideband audio transformers design by employing methods of artificial intelligence algorithms. This novel approach to audio transformers designing has a notable implication for problematics related to audio transformers complex design process. The authors are building on their previous research by trying to determine the trends which can be observed by selecting different secondary to primary windings ratio of evolutionary designed audio transformer. These trends can be useful at further optimization of the designing algorithms.


Differential Evolution Test Vector Voltage Gain Mechanical Issue Transformer Design 
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  1. 1.
    Pospisilik, M., Adamek, M.: Audio Transformers Simulation. In: Proceedings of the 16th WSEAS Multiconference, Kos, Greece (Accepted for publication, in print, 2012) Google Scholar
  2. 2.
    Pospisilik, M., Adamek, M.: Determining the parameter manufacturability. In: Proceedings of the 16th WSEAS Multiconference, Kos, Greece (Accepted for publication, in print 2012) Google Scholar
  3. 3.
    Kouril, L., Pospisilik, M., Adamek, M., Jasek, R.: Designing an Audio Transformer by Means of Evolutionary Algorithms. In: Proceedings of the 5th WSEAS World Congress on Applied Computing Conference, Faro, Portugal, pp. 133–138 (2012) ISBN 978-1-61804-089-3Google Scholar
  4. 4.
    Pospisilik, M., Kouril, L., Adamek, M., Zelinka, I., Jasek, R.: SOMA-Based Audio Transformers Optimization. In: Proceedings of the 18th International Conference on Soft Computing MENDEL 2012, Brno, Czech Republic, pp. 326–331 (2012) ISBN 978-80-214-4540-6. ISSN 1803-3814Google Scholar
  5. 5.
    Lampinen, J., Zelinka, I.: Mechanical Engineering Design Optimization by Differential Evolution. In: New Ideas of Optimization, 1st edn., McGraw-Hill, London (1999) ISBN 007-709506-5Google Scholar
  6. 6.
    Zelinka, I., Oplatkova, Z., Seda, M., Osmera, P., Vcelar, F.: Evolucni vypocetni techniky - principy a aplikace. BEN - technicka literatura, Praha (2008) ISBN 80-7300-218-3Google Scholar
  7. 7.
    Zelinka, I.: SOMA - Self-Organizing Migrating Algorithm. In: Onwubolu, G., Babu, B.V. (eds.) New Optimization Techniques in Engineering, pp. 3–540. Springer, Heidelberg (2004)Google Scholar
  8. 8.
    Varacha, P.: Innovative Strategy of SOMA Control Parameter Setting. In: Proceedings of the 12th WSEAS International Conference on Neural Networks, Fuzzy Systems, Evolutionary Computing & Automation. WSEAS Press, Timisoara (2011) ISBN 978-960-474-292-9Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Martin Pospisilik
    • 1
    Email author
  • Lukas Kouril
    • 1
  • Milan Adamek
    • 1
  • Ivan Zelinka
    • 2
  • Roman Jasek
    • 1
  1. 1.Faculty of Applied InformaticsTomas Bata University in ZlinZlinCzech Republic
  2. 2.Department of Computer Science, Faculty of Electrical Engineering and Computer ScienceVŠB-TUOOstravaCzech Republic

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