Altun HalisYalcinoz TankutTezekici Bekir Sami2019-08-012019-08-012000https://hdl.handle.net/11480/1391IEEE10th Mediterranean Electrotechnical Conference (MALECON2000) -- 29 May 2000 through 31 May 2000 -- Lemesos, Cyprus -- 57862In literature improvements in neural learning are reported on, which have been achieved through input data manipulation, based on entirely experimental studies. Theoretical background is not supplied for these studies and neural networks are employed as a 'black box' model. Within this work, this problem is highlighted and the impact of the modified training sets is evaluated in order to establish a theoretical background for the phenomenon. For this end, a number of binary training data is employed to show how does the learning process depend on data distribution within the training sets.eninfo:eu-repo/semantics/closedAccessConference Object25675692-s2.0-0034484211N/AWOS:000166106500138N/A