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Change in response time of neuronal populations with noise, synaptical interactions and stimulus frequency

Özsoy, Muhammet Ali | Uzuntarla, Muhammet | Özer, Mahmut


Neurons which are the fundamental elements of the nervous system, encode the information about stimulus they received from the external world by sensory system into action potential (spike) sequences before transmitting to the brain. In this study, a neuron population is modeled in mathematical manner and then first spike appearance time in a spike train is examined against changes in the characteristics of the periodic forcing. We also examine the effect of noise which stems from the biophysical structure of neurons and the effect of synaptic coupling which is the consequence of synaptic interaction of neurons with each other in th . . .e population to the appearance time of first spikes. The obtained results show that the mean response time of the population decreases with the increasing frequency. When the intensity of inherent noise in the neuronal environment increased, it shows a decreasing effect on the mean response only for low frequency range of the stimulus. Although the synaptic interaction coefficient does not affect substantially the mean response time of the population, it was shown that it is the fundamental parameter controlling the standard deviation of the response time Daha fazlası Daha az

Reliability and validity of turkish version of fibromyalgia participation questionnaire

Altan, L. | Celiker, R. | Ercan, I. | Birtane, M. | Akgün, Kübra | Zateri, C. | Tastekin, N.

Proceedings | 2017 | ANNALS OF THE RHEUMATIC DISEASES76 , pp.1380 - 1380

Annual European Congress of Rheumatology -- JUN 14-17, 2017 -- Madrid, SPAIN WOS: 000413181404194

Visual line tracking with vector field guidance for UAV

Köksal, Kerem | Surucu, Dilek | Surucu, Murat | Hacıoğlu, Rıfat


In this study, it is aimed to follow a visual route by an Unmanned Aerial Vehicle (UAV). The recognition of the predetermined line by using image processing algorithms and the process of following the route by using the method of Tangent Vector Field Guidance (TVFG) have been performed in indoor and outdoor experiments. UAV's following the correct route has been ensured by calculating the deflection caused by some factors such as wind and light which adversely affect the flight of UAV. In Vector Field Guidance method, the direction angles calculated by using the vector fields that will follow the line-shaped guide path are used. Whe . . .n the path to be followed has more than one direction instead of a single straight line, it is divided into sections which consist of straight lines, and by prioritizing these lines, the most dominant line is followed. In this study, it is aimed to provide a dynamic model by considering the tracking errors. As a result of the process adopted, UAV's autonomous flight is achieved by using the visual inputs and TVFG method, and the external disturbing factors are investigated Daha fazlası Daha az

Comparision of classifier performances in diagnosing congestive heart failure using heart rate variability

Narin, Ali | Özer, Mahmut | İşler, Yalçın


In this study, the performance of different discrimination algorithms in the analysis of heart rate variability that are used in discriminating the patients with congestive heart failure from normal subjects were investigated. Classifier algorithms of linear discriminant analysis, k-nearest neighbors, multilayer perceptron, radial basis functions and support vector machines were examined with different parameter values. As a result, the maximum classification accuracy of 91.56% was achieved by using multilayer perceptron with 11 neurons in hidden layer.

Real time detection of alternator failures using intelligent control systems

Uçar, Murat | Bayır, Raif | Özer, Mahmut

Proceedings | 2009 | ELECO 2009 - 6th International Conference on Electrical and Electronics Engineering , pp.646 - 649

On todays vehicles, dynamos are being left gradually and alternators take the turn instead for charging systems. Alternator is an electromechanical device which converts mechanical energy into electrical energy. Superior feature of alternators is that they can be charged on idling epoch and they have more output current. On the other hand by using diodes alternative current can be converted into direct current. Alternators are the main component of the charging system on modern vehicles. In this study, alternator failures are detected using fuzzy logic and artificial neural network. These are double diode failure, excessive current, . . . excessive stretch belt, loose belt, loose brush, regulator failure, short circuits on coils, one broken connection on rotor coil, two broken connection on rotor coil, broken connection on tridiode and tridiode short circuit. For detecting the failures, current, accumulator voltage, alternator voltage and the epoch number of the alternator is measured and alternator failure detection classification is implemented by designing an intelligent system inference according to these measured values Daha fazlası Daha az

Simulation of Parkinsonian Basal nuclei with network motifs

Çalım, Ali | Özer, Mahmut | Uzuntarla, Muhammet

Proceedings | 2017 | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 , pp.295 - 295

Nowadays, neurodegenerative diseases which affect human life quite negatively with motor, cognitive and psychiatric disorders are becoming widespread. One of the most common neurodegenerative disorder is Parkinson's disease. Recent electrophysiological experiments have shown that Basal Ganglia, a special region in the midbrain, is related to Parkinsonism. Beta frequency oscillations, which are important symptoms of Parkinson's disease, emerge intensively in Globus Pallidus and Subtalamus nuclei. In this study, anatomical connections of Globus Pallidus and Subtalamus are constructed computationally, and the cellular properties that g . . .ive rise to emergence of beta oscillations are investigated. © 2017 IEEE Daha fazlası Daha az

Effects of autapse and channel blockage on firing regularity in a biological neuronal network

Uzun, Rukiye | Özer, Mahmut

Proceedings | 2017 | Istanbul University - Journal of Electrical and Electronics Engineering17 , pp.3069 - 3073

In this paper; the effects of autapse (a kind of self-synapse formed between the axon of the soma of a neuron and its own dendrites) and ion channel blockage on the firing regularity of a biological small-world neuronal network, consists of stochastic Hodgkin-Huxley neurons, are studied. In this study, it is assumed that all of the neurons on the network have a chemical autapse and a constant membrane area. Obtained results indicate that there are different effects of channel blockage and parameters of the autapse on the regularity of the network, thus on the temporal coherence of the network. It is found that the firing regularity . . .of the network is decreased with the sodium channel blockage while increased with potassium channel blockage. Besides, it is determined that regularity of the network augments with the conductance of the autapse Daha fazlası Daha az

Ultrasonic signal delay determination for distance estimation in underwater space [Sualti Uzaylarda Mesafe Kestirimi İçin Ultrasonik İşaret Gecikmesinin Belirlenmesi]

Onur, Tuğba Özge | Hacıoğlu, Rıfat

Proceedings | 2017 | 2017 25th Signal Processing and Communications Applications Conference, SIU 2017 , pp.3069 - 3073

Reverberation and multipath propagation afîect the accuracy of time of flight (TOF) estimation in confined underwater medium. In this paper, time delay has been estimated by obtaining the transmitted signal and first echo signal from measured signal acquised by using a wideband transducer with 5 MHz central frequency. Cross-correlation (CC) and generalized cross-correlation (GCC) methods have been applied to the obtained signals and their performances have been compared. The results show that GCC method has better performance for time delay estimation in confined underwater medium where multipath propagation and reverberation are se . . .vere. © 2017 IEEE Daha fazlası Daha az

Effect of filtering on processing of thermal lens fringes by single sideband modulation technique

Emir, Ahmet | Saraç, Zehra


This paper proposes the use of single sideband modulation technique with Gaussian and band pass fillers for the analysis of the thermal lens fringe to obtain the map of the refractive index change. Maps of the refractive index and phase change are achieved by using single side band modulation technique with Gaussian and band pass filters. Consequently it is seen that single side band modulation technique with Gaussian filter shows more accurate results.

Prediction of the optimal threshold value in DF relay selection schemes based on artificial neural networks

Kara, Ferdi | Kaya, Hakan | Erkaymaz, Okan | Öztürk, Ertan

Proceedings | 2016 | Proceedings of the 2016 International Symposium on INnovations in Intelligent SysTems and Applications, INISTA 2016 , pp.3069 - 3073

In wireless communications, the cooperative communication (CC) technology promises performance gains compared to traditional Single-Input Single Output (SISO) techniques. Therefore, the CC technique is one of the nominees for 5G networks. In the Decode-And-Forward (DF) relaying scheme which is one of the CC techniques, determination of the threshold value at the relay has a key role for the system performance and power usage. In this paper, we propose prediction of the optimal threshold values for the best relay selection scheme in cooperative communications, based on Artificial Neural Networks (ANNs) for the first time in literatur . . .e. The average link qualities and number of relays have been used as inputs in the prediction of optimal threshold values using Artificial Neural Networks (ANNs): Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) networks. The MLP network has better performance from the RBF network on the prediction of optimal threshold value when the same number of neurons is used at the hidden layer for both networks. Besides, the optimal threshold values obtained using ANNs are verified by the optimal threshold values obtained numerically using the closed form expression derived for the system. The results show that the optimal threshold values obtained by ANNs on the best relay selection scheme provide a minimum Bit-Error-Rate (BER) because of the reduction of the probability that error propagation may occur. Also, for the same BER performance goal, prediction of optimal threshold values provides 2dB less power usage, which is great gain in terms of green communication. © 2016 IEEE Daha fazlası Daha az

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