Comparison of MLP neural network and neuro-fuzzy system in transcranial Doppler signals recorded from the cerebral vessels.
Transcranial Doppler signals recorded from cerebral vessels of 110 patients were transferred to a personal computer by using a 16 bit sound card. Spectral analyses of Transcranial Doppler signals were performed for determining the Multi Layer Perceptron (MLP) neural network and neuro Ankara-fuzzy system inputs. In order to do a good interpretation and rapid diagnosis, FFT parameters of Transcranial Doppler signals classified using MLP neural network and neuro-fuzzy system. Our findings demonstrated that 92% correct classification rate was obtained from MLP neural network, and 86% correct classification rate was obtained from neuro-fuzzy system.
Hardalaç
Firat
F
Department of Computer Engineering, Faculty of Engineering, Kirikkale University, Kirikkale, Turkey. hardalac@gmail.com
D002550:Cerebral Veins / Q000000981:diagnostic imaging*; D017143:Fuzzy Logic; D006801:Humans; D016571:Neural Networks, Computer; D012815:Signal Processing, Computer-Assisted; D017585:Ultrasonography, Doppler, Transcranial