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Genetic minimisation of peak-to-peak level of a complex multi-tone signal

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Języki publikacji
EN
Abstrakty
EN
This paper presents results of evolutionary minimisation of peak-to-peak value of a?multi-tone signal. The signal is the sum of multiple tones (channels) with constant amplitudes and frequencies combined with variable phases. An exemplary application is emergency broadcasting using widely used analogue broadcasting techniques: citizens band (CB) or VHF FM commercial broadcasting. The work presented illustrates a?relatively simple problem, which, however, is characterised by large combinatorial complexity, so direct (exhaustive) search becomes completely impractical. The process of minimisation is based on genetic algorithm (GA), which proves its usability for given problem. The final result is a?significant reduction of peak-to-peak level of given multi-tone signal, demonstrated by three real-life examples.
Rocznik
Strony
621--629
Opis fizyczny
Bibliogr. 19 poz., wykr., rys., tab.
Twórcy
  • Faculty of Automatic Control, Electronics and Computer Programming Institute of Electronics, Silesian University of Technology Akademicka 16 Street, 44-100 Gliwice, Poland
Bibliografia
  • [1] D.E. Goldberg, Genetic Algorithms in Search, Optimization & Machine Learning, Addison-Wesley, 1989.
  • [2] D. MacKay, Information Theory, Inference and Learning Algorithms, CUP, 2003.
  • [3] J. Arabas, “Wykłady z algorytmów ewolucyjnych”, WNT, 2001, ISBN 83‒204‒2604‒9 (in Polish).
  • [4] M. Anedda, A. Meloni, and M. Murroni, “64-APSK Constellation and Mapping Optimization for Satellite Broadcasting Using Genetic Algorithms”, IEEE Transactions on Broadcasting, 2016, Vol. 62, No. 1, p. 1‒9, DOI 10.1109/TBC.2015.2470134.
  • [5] B. Biswal, T.K. Panda, S. Hasan, P.K. Dash, and B.K. Panigrahi, “Nonstationary power signal processing and pattern recognition using genetic algorithm”, 2007 6th International Conference on Information, Communications & Signal Processing, Singapore, 2007, pp. 1‒5, DOI: 10.1109/ICICS.2007.4449543.
  • [6] S. Cerutti and C. Marchesi, Soft Computing in Signal and Data Analysis: Neural Networks, NeuroFuzzy Networks, and Genetic Algorithms in Advanced Methods of Biomedical Signal Processing, IEEE, 2011, DOI: 10.1002/9781118007747.ch21.
  • [7] L. Chruszczyk, “Wavelet Transform in Fault Diagnosis of Analogue Electronic Circuits in Advances in Wavelet Theory and Their Applications in Engineering”, Physics and Technology, ed. Dumitru Baleanu, InTech, Croatia, 04.2012, p. 197–220, DOI 10.5772/36423, ISBN 978‒953‒51‒0494‒0.
  • [8] L. Chruszczyk, “Tolerance Maximisation in Fault Diagnosis of Analogue Electronic Circuits”, 20th European Conference on Circuit Theory and Design (ECCTD), Linköping, 2011, pp. 881–884 + CD p. 914–917, ISBN 978‒1‒4577‒0616‒5.
  • [9] L. Chruszczyk, D. Grzechca, and J. Rutkowski, “Finding of optimal excitation signal for testing of analog electric circuits”, Bull. Pol. Ac.: Tech. 55 (3), 2007, p. 273‒280.
  • [10] T. Golonek, D. Grzechca, and J. Rutkowski, “Application of genetic programming to edge detector design”, IEEE International Symposium on Circuits and Systems (ISCAS), Island of Kos, 2006, proc. Piscataway Institute of Electrical and Electronics Engineers, pp. 4683‒4686.
  • [11] T. Golonek and J. Rutkowski, “Genetic-algorithm-based method for optimal analog test points selection”, IEEE Trans. Circuits Syst., II 2007, vol. 54, iss. 2, p. 117‒121.
  • [12] F.M. Janeiro and P.M. Ramos, “Impedance Measurements Using Genetic Algorithms and Multiharmonic Signals”, in IEEE Transactions on Instrumentation and Measurement 58 (2), pp. 383‒388, 2009, DOI: 10.1109/TIM.2008.2005077.
  • [13] M. Korzybski and M. Ossowski, “Evolutionary stimuli selection for fault diagnosis in analog circuits”, Przegląd Elektrotechniczny 87 (10), p. 167‒170, 2011.
  • [14] M. Lixia, M. Murroni, and V. Popescu, “PAPR reduction in multicarrier modulations using Genetic Algorithms”, 12th International Conference on Optimization of Electrical and Electronic Equipment (OPTIM), Brasov, 2010, pp. 938‒942, DOI 10.1109/OPTIM.2010.5510543.
  • [15] A. Meloni and M. Murroni, “On the genetic optimization of APSK constellations for satellite broadcasting”, IEEE International Symposium on Broadband Multimedia Systems and Broadcasting, Beijing, 2014, pp. 1‒6, DOI 10.1109/BMSB.2014.6873465.
  • [16] M. Murroni, “Performance analysis of modulation with unequal power allocations over fading channels: A genetic algorithm approach”, 14th European Wireless Conference, Prague, 2008, pp. 1‒6, DOI 10.1109/EW.2008.4623838.
  • [17] P. Subbaraj, S.S. Sankar, and S. Anand, “Parallel Genetic Algorithm for VLSI Standard Cell Placement”, 2009 International Conference on Advances in Computing, Control and Telecommunication Technologies, Trivandrum, 2009, pp. 80‒84, DOI:10.1109/ACT.2009.30.
  • [18] M. Tadeusiewicz, S. Hałgas, and M. Korzybski, “Multiple catastrophic fault diagnosis of analog circuits considering the component tolerances”, Int. Journal of Circuit Theory and Applications 40 (10), p. 1041‒1052, 2012.
  • [19] M. Woźniak and D. Połap, “On Some Aspects of Genetic and Evolutionary Methods for Optimization Purposes”, International Journal of Electronics and Telecomm. (IJET) 61 (1),2015.
Uwagi
PL
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-f218473c-53cf-429d-bf41-90a2837b5272
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