Opposition-based shuffled PSO with passive congregation applied to FM matching synthesis

2011 IEEE Congress of Evolutionary Computation, CEC 2011

Volumn , Issue , 2011, Pages 2775-2781

  Munoz, Daniel M ^a   Llanos, Carlos H ^a   Dos S Coelho, Leandro ^b   Ayala Rincon, Mauricio ^a  

^a UNIVERSITY OF BRASILIA   (Brazil)

^b PONTIFICAL CATHOLIC UNIVERSITY OF PARANÁ   (Brazil)

Author keywords

FM matching synthesis; Global optimization; Opposition based learning; Particle swarm optimization

Indexed keywords

EXPERIMENTAL KNOWLEDGE; HUMAN VOICE; HYBRID PARTICLE SWARM OPTIMIZATION; HYBRID PARTICLE SWARM OPTIMIZATION ALGORITHM; MULTIMODAL OPTIMIZATION PROBLEMS; MUSICAL SOUNDS; OPPOSITION-BASED LEARNING; OPTIMIZATION ALGORITHMS; PARTICLE SWARM; PASSIVE CONGREGATION; QUALITY OF SOLUTION; SIMULATION RESULT; SYNTHESIS PROBLEMS; TIME-CONSUMING PROCESS; TRIAL AND ERROR;

ALGORITHMS; GLOBAL OPTIMIZATION; MATHEMATICAL OPERATORS; MUSICAL INSTRUMENTS;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 80051988720     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CEC.2011.5949966     Document Type: Conference Paper

References (22)

1. J. Chowning, "The synthesis of complex audio spectra by means of frequency modulation", J. Audio Eng. Soc., vol. 21, pp. 526-534, 1973.
2. A. Horner, "Nested modulator and feedback FM matching of instrument tones", IEEE Trans. on Speech and Audio Processing, vol. 6, no. 4, pp. 398-409, 1998. (Pubitemid 128720670)
3. F. Herrera and M. Lozano, "Gradual distributed real-coded genetic algorithms", IEEE Trans. on Evolutionary Computation, vol. 4, no. 1, pp. 43-63, 2000.
4. Y. Lai, S. Jeng, D. Liu, and Y. Liu, "Automated optimization of parameters for FM sound synthesis with genetic algorithms", in int. Workshop on Computer Music and Audio Technology, 2006, pp. 33-38, Taipei, Taiwan.
5. T. Mitchell, "An exploration of evolutionary computation applied to frequency modulation audio synthesis parameter optimisation", Ph. D. dissertation, Bristol Institute of Technology, Faculty of Environment and Technology, University of the West of England, 2010, Bristol, UK.
6. J. McDermott, "Evolutionary computation applied to the control of sound synthesis", Ph. D. dissertation, The University of Limerick, 2008, Ireland.
7. J. Riget and J. Vesterstrom, "A diversity-guided particle swarm optimizer - the ARPSO", EVALife, Tech. Rep., 2002, Aarhus, Denmark.
8. M. Pant, R. Radha, and V. Singh, "A simple diversity guided particle swarm optimization", in Proc. IEEE Conf. on Evolutionary Computation, 2007, pp. 3294-3299, Singapore.
9. F. van den Bergh, "An analysis of particle swarm optimizers", Ph. D. dissertation, Department of Computer Science, University of Pretoria, 2002, South Africa.
10. R. Mendes, "Population topologies and their influence in PSO", Ph. D. dissertation, Universidade do Minho, 2004, Portugal.
11. J. Voit, "Otimização por enxame de partículas com congregação passiva seletiva", Ph. D. dissertation, Universidade Federal do Rio de Janeiro, 2010, Rio de Janeiro, Brasil (in Portuguese).
12. J. Parrish and W. Hamner, Animal Groups in Three Dimensions. Cambridge University Press, 1997, Cambridge, UK.
13. S. He, Q. Wu, J. Wen, J. Saunders, and R. Paton, "A particle swarm optimizer with passive congregation", Bio-Systems Iternational Journal, vol. 78, pp. 135-147, 2004. (Pubitemid 39536138)
14. H. Tizhoosh, "Opposition-based learning a new scheme for machine intelligence", in Proc. Int. Conference on Computational Intelligence for Modelling, Control and Automation, 2005, pp. 695-701, Vienna, Austria.
15. H. R. S. Al-Qunaieer, F. S. Tizhoosh, "Opposition based computing a survey", in Proc. Int. Joint Conference on Neural Networks, 2010, pp. 1098-7576, Barcelona, Spain.
16. S. Rahnamayan, H. Tizhoosh, and M. Salama, "Opposition versus randomness in soft computing techniques", Journal Applied Soft Computing, vol. 8, pp. 906-918, 2008. (Pubitemid 350266486)
17. A. Malisia and T. H. R., "Applying opposition-based ideas to the ant colony system", in Proc. IEEE Swarm Intelligence Symposium, 2007, pp. 182-189, Honolulu, HI. (Pubitemid 47431838)
18. H. Jabeen, Z. Jalil, and A. Baig, "Opposition based initialization in particle swarm optimization (O-PSO)", in Proc. ACM Conference on Genetic and Evolutionary Computation, 2009, pp. 2047-2052, Montreal, Canada.
19. M. Eusuff and K. Lansey, "Optimization of water distribution network design using the shuffled frog leaping algorithm", J. Water Resources Planning & Management, vol. 129, no. 3, pp. 210-225, 2003. (Pubitemid 36562716)
20. M. Eusuff, K. Lansey, and F. Pasha, "Shuffled frog leaping algorithm: a memetic meta-heuristic for discrete optimization", J. of Eng. Optimization, vol. 38, no. 2, pp. 129-154, 2006. (Pubitemid 43279596)
21. J. Durillo, J. Garćia-Nieto, A. J. Nebro, C. Coello, F. Luna, and E. Alba, "Multi-objective particle swarm optimizers: An experimental comparison", in Proc. of the Int. Conference on Evolutionary Multi-Criterion Optimization, 2009, pp. 495-509, Nantes, France.
22. J. Demšar, "Statistical comparison of classifiers over multiple data sets", J. Machine Learning Research, vol. 7, pp. 1-30, 2006. (Pubitemid 43022939)