Comparison of split complex-valued metaheuristic optimization algorithms for system identification problem [Sistem tanimlama problemi için bölünmüş kompleks-degerli sezgisel eniyileme algoritmalarinin karşilaştirilmasi]
Küçük Resim Yok
Tarih
2018
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
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. © 2018 IEEE.
Açıklama
Aselsan;et al.;Huawei;IEEE Signal Processing Society;IEEE Turkey Section;Netas
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- -- 137780
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 -- 2 May 2018 through 5 May 2018 -- -- 137780
Anahtar Kelimeler
Complex-valued Signals, Split Complex-valued Metaheuristic Algorithms, System Identification
Kaynak
26th IEEE Signal Processing and Communications Applications Conference, SIU 2018
WoS Q Değeri
Scopus Q Değeri
N/A
