Comparison of Split Complex-Valued Metaheuristic Optimization Algorithms for System Identification Problem

Menguc E. C., Peker M., Cinar S.

26th IEEE Signal Processing and Communications Applications Conference (SIU), İzmir, Turkey, 2 - 05 May 2018 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Volume:
  • Doi Number: 10.1109/siu.2018.8404771
  • City: İzmir
  • Country: Turkey
  • Kayseri University Affiliated: No


Since some of the real world problems include phase and amplitude information, complex modeling is more suitable. In this study, the well-used particle swarm optimization, simulated annealing and genetic algorithm are designed in a split form in order to process complex-valued signals. The performances of the algorithms are comparatively tested on two different system identification problems for different noise levels. Simulation results show that the split complex-valued metaheuristic algorithms produce results which are almost close to the weights of both unknown systems.