Browsing Mühendislik Fakültesi by Subject "Neurosciences & Neurology"

Now showing items 1-5 of 8

Automatic seizure detection in EEG using logistic regression and artificial neural network

Köklükaya, Etem (ELSEVIER SCIENCE BV, 2005)

The detection of epileptiform discharges in the EEG is an important component in the diagnosis of epilepsy. In this study, multiple signal classification (MUSIC), autoregressive (AR) and periodogram methods were used to ...
Real-Time Monitoring and Fault Diagnosis of a Low Power Hub Motor Using Feedforward Neural Network

Mehmet Simsir; Raif Bayjr; Uyaroğlu, Yılmaz (HINDAWI LTD, 2016)

Low power hub motors are widely used in electromechanical systems such as electrical bicycles and solar vehicles due to their robustness and compact structure. Such systems driven by hub motors (in wheel motors) encounter ...
Solving Single Machine Total Weighted Tardiness Problem with Unequal Release Date Using Neurohybrid Particle Swarm Optimization Approach

Çakar, Tarık; Köker, Raşit (HINDAWI PUBLISHING CORPORATION, 2015)

A particle swarm optimization algorithm (PSO) has been used to solve the single machine total weighted tardiness problem (SMTWT) with unequal release date. To find the best solutions three different solution approaches ...
Wavelet neural network classification of EEG signals by using AR model with MLE preprocessing

Köklükaya, Etem (PERGAMON-ELSEVIER SCIENCE LTD, 2005)

Since EEG is one of the most important sources of information in therapy of epilepsy, several researchers tried to address the issue of decision support for such a data. In this paper, we introduce two fundamentally different ...
Weak signal propagation through noisy feedforward neuronal networks

Köklükaya, Etem (LIPPINCOTT WILLIAMS & WILKINS, 2010)

We determine under which conditions the propagation of weak periodic signals through a feedforward Hodgkin-Huxley neuronal network is optimal. We find that successive neuronal layers are able to amplify weak signals ...