activity
20112018
most citedAdaptive stimulus design for dynamic recurrent neural network models

2 citations · 3 across the 6 of their papers we have counts for

collaborators

6 papers

q-bio.NC2018

Fitting a recurrent dynamical neural network to neural spiking data: Tackling with the sigmoidal gain function issues

Resat Ozgur Doruk

This is a continuation of a recent study on the modeling of the information coding in sensory system in the brain. The data from a sensory neurons are available as discrete spike t…

q-bio.NC2017

Fitting of dynamic recurrent neural network models to sensory stimulus-response data

R. Ozgur Doruk, Kechen Zhang

We present a theoretical study aiming at model fitting for sensory neurons. Conventional neural network training approaches are not applicable to this problem due to lack of contin…

q-bio.NC2016★ 2 cited

Adaptive stimulus design for dynamic recurrent neural network models

R. Ozgur Doruk, Kechen Zhang

We present a theoretical application of an optimal experiment design (OED) methodology to the development of mathematical models to describe the stimulus-response relationship of s…

math.OC2016

Projective DC Motor Control Under Disturbance Torques

Ismael Zuglem, Resat Ozgur Doruk

In this study, we will present the design of a linear DC motor controller by projective linear qudratic servo feedback (P-LQSF) and analyze its stability through the notion of inpu…

math.DS2011

SDRE Based Attitude Control Using Modified Rodriguez Parameters

R. Ozgur Doruk

The purpose of this paper is to present an application of the State Dependent Riccati Equation (SDRE) method to satellite attitude control where the satellite kinematics is modeled…

q-bio.NC2011★ 1 cited

Control of the repetitive firing in the squid giant axon using electrical fields

Resat Ozgur Doruk

In this research, the aim is to develop a repetitive firing stopper mechanism using electrical fields exerted on the fiber. The Hodgkin - Huxley nerve fiber model is used for model…