Ceylan, Murat2020-03-262020-03-262011978-988-19251-4-52078-0958https://hdl.handle.net/20.500.12395/26241World Congress on Engineering (WCE 2011) -- JUL 06-08, 2011 -- Imperial Coll, London, UNITED KINGDOMThis study presents a new version of complex valued artificial neural networks (CVANN) for the complex valued pattern recognition and classification. Proposed new method is called as combined complex-valued artificial neural network (CCVANN) which is a combination of two complex valued artificial neural networks. To check the validation of proposed method, complex-valued XOR benchmark problem is used. The accuracy of the CCVANN model is more satisfactory as compared to the existing studies in the literature. Moreover the proposed CCVANN models' results have lower recognition error than using a single CVANN model.eninfo:eu-repo/semantics/closedAccessComplex-valued artificial neural networkcomplex-valued XOR problemConference Object955959N/AWOS:000393012800007N/A