Menguc E.C.Peker M.Cinar S.2019-08-012019-08-0120189.78154E+12https://dx.doi.org/10.1109/SIU.2018.8404771https://hdl.handle.net/11480/1632Aselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netas26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- -- 137780Since 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. © 2018 IEEE.trinfo:eu-repo/semantics/closedAccessComplex-valued SignalsSplit Complex-valued Metaheuristic AlgorithmsSystem IdentificationConference Object1410.1109/SIU.2018.84047712-s2.0-85050820312N/A