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Bulunan: 16 Adet 0.081 sn
Dergi Adı : 26th IEEE Signal Pro ... ✕
Koleksiyon [13]
İlgili Araştırmacılar [7]
Ambargo Durumu [1]
Tam Metin [2]
Yazar [28]
Yayın Türü [2]
Yayın Yılı [1]
Yayın Dili [1]
Dergi Adı [1]
Yayıncı [1]
Konu Başlıkları [58]

Effect of channel noise and dynamic synapse structure on latency dynamics in neural system

Çalım, Ali | Özer, Mahmut | Uzuntarla, Muhammet

Experimental and theoretical studies in recent years suggest that the first spike latency is an effective information carrier and contains more neural information than other spikes. Noise Delayed Decay (NDD) phenomenon emerges when the first spike latency of the neuron exposed to the periodic driving is maximum at a certain noise intensity interval. In this study, the latency dynamics of a single Hodgkin-Huxley neuron is investigated under periodic driving, background activity through dynamic synapses, and channel noise. The system response with first spike latency is investigated as a functio ...Daha fazlası

Bildiri 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 1123 Görüntülenme
Erişime Açık

Classification of refractive disorders from electrooculogram (EOG) signals by using data mining techniques

Kaya, Ceren | Erkaymaz, Okan | Ayar, Orhan | Özer, Mahmut

Refractive disorders are common health problems in the community and they are the most important cause of visual impairment. In this study, it was aimed to classify the individuals who have hypermetropia and myopia refractive disorders or not. For this, horizontal and vertical Electrooculogram (EOG) signal data from the right and left eyes of the individuals were used. The performance of the data was investigated by using Logistic Regression (LR), Naive Bayes (NB), Random Forest (RF) and REP Tree (RT) data mining methods. According to the obtained results, REP Tree method has shown the most su ...Daha fazlası

Bildiri 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 1550 Görüntülenme

Effects of autapse on weak signal detection in FFL network motifs

Baysal, Veli | Yılmaz, Ergin

In this paper, effects of autapse on signal detection capacity of Izhikevich neuron in feed-forward-loop network motifs are investigated. Obtained results showed that autapse significantly enchances singal detection of Izhikevich neuron at proper autaptic time delay values compared without autapse. Also, it is seen that feed-forward-loop motifs have significant effects on signal detection ability of Izhikevich neuron. It is obtained that signal detection of Izhikevich neuron are best in T1 feed-forward-loop motif. © 2018 IEEE.

Bildiri 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 819 Görüntülenme

Vibrational resonance in a Hodgkin-Huxley neuron under electromagnetic induction

Baysal, Veli | Yılmaz, Ergin

In this paper, effects of electromagnetic induction on vibrational resonance phenomenon in a Hodgkin-Huxley neuron are investigated. By stimulating Hodgkin-Huxley neuron with both high-frequency signal and low-frequency weak signal, its weak signal detection capacity have been investigated under electromagnetic induction effect. Obtained results show that electromagnetic induction causes decreasing of the amplitude of vibrational resonance effect emerging depending on the amplitude of high frequency signal. Also, vibrational resonance phenomenon occurs at smaller amplitudes of high frequency s ...Daha fazlası

Bildiri 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 1021 Görüntülenme

Subthreshold signal detection in heterogeneous neural networks

Çalım, Ali | Özer, Mahmut | Uzuntarla, Muhammet

In this study, effects of the heterogeneity in neuronal networks and subthreshold signal features on subthreshold signal detection in the nervous system is investigated. As most of studies in the literature investigate the subject by considering neuron populations as homogenous systems, in this study, the populations are considered as heterogeneous in terms of neuronal excitability. The information processing performance of the neuron populations is systematically studied by using mathematical equations for modeling the dynamics of the neurons, which are basic units of the system. As a result ...Daha fazlası

Bildiri 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 1184 Görüntülenme

Hammerstein model performance of three axes gimbal system on Unmanned Aerial Vehicle (UAV) for route tracking [Rota takibinde insansiz hava araci üzerinde bulunan üç eksenli yalpa sisteminin hammerstein model başarimi]

Altan A. | Hacioglu R.

In this study, focuses on the non-linear Hammerstein model under external disturbance with white Gaussian noise based on the experimental input (motor velocities) and output (end effector position) data of the three axes gimbal system on the Unmanned Aerial Vehicle (UAV), which is autonomously moving for route tracking. The performance of UAV in reaching the target point on a planned route in sinusoidal form in avoiding obstacles, depends on the route tracking performance of the three axes gimbal system on the UAV. In intelligence activities such as exploration and surveillance, Hammerstein an ...Daha fazlası

Konferans Nesnesi 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 321 Görüntülenme

Classification of power quality events signals with pattern recognition methods by using Hilbert transform and genetic algorithms [Güç kalitesi bozulma sinyallerinin hilbert dönüşümü ve genetik algoritmalar kullanilarak örüntü tanima yöntemleri ile siniflandirilmasi]

Karasu S. | Sarac Z.

In this study, instantaneous envelope, phase and frequency series are obtained by Hilbert transform for Power Quality (PQ-Power Quality) disturbances signals. Rms, Thd, energy, entropy and statistical properties are applied to these series. With the wrapper feature selection approach, a set of features is obtained that has a small number of feature subset and a high performance from 36 features. Genetic Algorithm (GA) is used as a search algorithm and the classifier algorithm is K nearest neighborhood (KNN). Support Vector Machines (SVM) for selected features are also used in the classificatio ...Daha fazlası

Konferans Nesnesi 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 347 Görüntülenme

Occupancy detection from temperature, humidity, light, CO2 and humidity ratio measurements using machine learning techniques [Makine Ögrenmesi Teknikleri ile Sicaklik, Nem, Aydinlik Seviyesi, CO2 ve Nem Orani Ölçümlerinden Varlik Tespiti]

Palabas T. | Eroglu K.

Order to save energy and to use energy resources efficiently, automatic occupancy determination based on sensor information is performed and energy is adjusted according to the demand in a closed area. In this study is used records consisting of T (temperature), H (humidity), L (light level), CO2 (carbon dioxide) and R (humidity ratio) sensor data. Occupancy analysis based on sensor data has been performed with REPTree (Reduced Error Pruning tree), NB (Naive Bayes), SVM (Support Vector Machine) and KNN (K Nearest Neighbor) classification algorithms. The highest classification success (97.98%) ...Daha fazlası

Konferans Nesnesi 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 288 Görüntülenme

Online dead body detection experiment with an unmanned underwater vehicle [Bir insansiz sualti araci ile çevirimiçi ceset tanilama deneyi]

Berik M. | Kartal S.K.

In this study, real-time online body detection under water was conducted using an unmanned underwater observation tool. According to the underwater position of the vehicle, data from the vehicle camera is provided to identify different body parts of a body in a real-time video stream. Here we present an approach for underwater human body detection based on the use of highly educated classifiers. The algorithm's performance in real time video shooting of the car is optimized to reduce the false positive rate by aiming to identify a corpse part of each picture frame. According to the results obt ...Daha fazlası

Konferans Nesnesi 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 273 Görüntülenme

The usage of artificial neural network as post processing algorithm in digital holography [Sayisal holografide yapay sinir aglarinin son işlem algoritmasi olarak kullanilmasi]

Kaya G.U. | Sarac Z.

The purpose of this study is to train the reconstructed sound waves, which is obtained from recording holograms via digital holography, and reduce the noise from this sound wave without using noise Altering techniques. The noise reduction is achieved by approximating the reconstructed sound wave trained by YSA to the actaul recording sound wave. A network topology is created for training and the system was tested. The performance of the system is given by showing how closely the sound wave trained by YSA approaches the actual sound wave. © 2018 IEEE.

Konferans Nesnesi 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 280 Görüntülenme

Choose of wart treatment method using Naive Bayes and k-nearest neighbors classifiers [Naive Bayes ve En Yakin k Komsu Siniflandiricilari ile Sigil Tedavi Yöntemi Seçimi]

Uzun R. | Isler Y. | Toksan M.

In this study, the success of cyrotheraphy and immunotherapy methods on common warts and plantar warts were predicted among 180 patients using machine learning methods. As a classifier, Naive Bayes and k-nearest neighbors with different neighborhood values of k were experimented. Data sets that are online available via Internet were used in the study. As a result, whether the treatment method by considering given features will give positive result could be estimated with the accuracy of 80% by using k-nearest neighbors classifier with the neighborhood value of k=7. © 2018 IEEE.

Konferans Nesnesi 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 302 Görüntülenme

Computer-assisted diagnosis of vertebral column diseases by adaptive neuro-fuzzy inference system

Uzun, Rukiye | İşler, Yalçın | Erkaymaz, Okan | Kocadayı, Yasemin

In this study, a clustering algorithm based on adaptive neural fuzzy inference system (ANFIS) was used for computer-assisted diagnosis of the vertebral column disorder from machine learning databases of UCI (University of California Irvine). Features of pelvic incidence, pelvic tilt and lumbar lordosis angle given in this dataset was applied to the inputs of the algorithm. The performance of algorithm was evaluated using mean square error and regression coefficient criteria to discriminate patients with vertebral column disease from healthy subjects. As a result, the classification performance ...Daha fazlası

Bildiri 2018 26th IEEE Signal Processing and Communications Applications Conference, SIU 2018 , pp. 1 - 4 960 Görüntülenme
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