@article{article_553279, title={AN IMPROVED WIENER MODEL FOR SYSTEM IDENTIFICATION}, journal={Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi}, volume={9}, pages={796–810}, year={2020}, DOI={10.28948/ngumuh.553279}, author={Mete, Selçuk and Zorlu, Hasan and Özer, Şaban}, keywords={system identification, wiener, hybrid model, optimization}, abstract={<p class="Abstract" style="margin-top:0cm;margin-right:21.15pt;margin-bottom:.0001pt;margin-left:21.3pt;"> <span lang="en-gb" xml:lang="en-gb">Wiener block structure is formed by cascade
of linear and nonlinear models. A novel and improved Wiener model </span> <span lang="en-gb" xml:lang="en-gb">structure </span> <span lang="en-gb" xml:lang="en-gb">for system identification area is proposed in this </span> <span lang="en-gb" xml:lang="en-gb">study. In proposed </span> <span lang="en-gb" xml:lang="en-gb">Wiener model </span> <span lang="en-gb" xml:lang="en-gb">, Finite Impulse Response
(FIR) model is used as linear part and Soft Switching based Hybrid (SSH) model
is used as nonlinear part. The SSH </span> <span lang="en-gb" xml:lang="en-gb">structure consists of a Second Order Volterra (SOV)
nonlinear model, a Memoryless Polynomial (MP) nonlinear model, and a
soft-switching part through a Neuro-Fuzzy (NF) network. </span> <span lang="en-gb" xml:lang="en-gb">In simulation studies, different types systems are identified by
presented novel model. In addition to the mentioned identified systems, the
performance of the improved model is also compared with Volterra model and
Wiener models presented in the literature. </span> <span lang="en-gb" xml:lang="en-gb">Simulation results find out
the success of the proposed model. </span> </p> <p> </p>}, number={2}, publisher={Nigde Omer Halisdemir University}