Browsing by KHAS Author "Tander, Baran"
Now showing items 1-11 of 11
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A numerical method for frequency determination in the astable cellular neural networks with opposite-sign templates
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Publisher and Date:(IEEE, 2006)In this study a numerical method is proposed to determine the oscillation frequencies in the astable cellular neural networks with opposite-sign templates [1]. This method depends on the training of a multilayer perceptron that uses various template coefficients and the correspondant frequency values as inputs and outputs. First of all a frequency surface is obtained from templates and then training samples are picked from this surface in order to apply to multilayer perceptron. The effects of the ...
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Amplitude and Frequency Modulations with Cellular Neural Networks
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Publisher and Date:(Springer, 2015)Amplitude and frequency modulations are still the most popular modulation techniques in data transmission at telecommunication systems such as radio and television broadcasting gsm etc. However the architectures of these individual systems are totally different. In this paper it is shown that a cellular neural network with an opposite-sign template can behave either as an amplitude or a frequency modulator. Firstly a brief information about these networks is given and then the amplitude and frequency ...
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Analytical approaches for the amplitude and frequency computations in the astable cellular neural networks with opposite sign templates
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Publisher and Date:(IEEE, 2007)In this paper, by using surface fitting methods, analytical approaches for amplitudes and frequencies of the x(1,2)(t) "States" in a simple dynamical neural network called "Cellular Neural Network with Opposite Sign Templates" which was proposed by Zou and Nossek [1], are obtained under oscillation conditions. The mentioned explicit expressions are employed in a cellular neural network based, amplitude and frequency tuneable oscillator design.
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Channel Equalization with Cellular Neural Networks
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Publisher and Date:(IEEE, 2010)In this paper a dynamic neural network structure called Cellular Neural Network (CNN) is employed for the equalization in digital communication. It is shown that this nonlinear system is capable of suppressing the effect of intersymbol interference (ISI) and the noise at the channel. The architecture is a small-scaled simple CNN containing 9 neurons thus having only 19 weight coefficients. Proposed system is compared with linear transversal filters as well as with a Multilayer Perceptron (MLP) ...
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Design and Implementation of a Cellular Neural Network Based Oscillator Circuit
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Publisher and Date:(World Scientific and Engineering Acad and Soc, 2009)In this paper, a novel inductorless oscillator circuit with negative feedbacks, based on a simple version of a "Cellular Neural Network" (CNN) called "CNN with an Opposite Sign Template" (CNN-OST) is designed and implemented. The system is capable of generating quasi-sine oscillations with tuneable amplitude and frequency which can't be provided at the same time in the conventional oscillator circuits.
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Design and implementation of a negative feedback oscillator circuit based on a Cellular Neural Network with an Opposite Sign Template
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Publisher and Date:(2010)In this paper explicit amplitude and frequency expressions for a Cellular Neural Network with an Opposite-Sign Template (CNN-OST) under oscillation condition are derived and a novel inductorless oscillator circuit with negative feedbacks based on this simple structure is designed and implemented. The system is capable of generating quasi-sine signals with tuneable amplitude and frequency which can't be provided at the same time in the classical oscillator circuits.
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Hücresel sinir ağları için gerilim kaynaklı hücre modelleri
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Publisher and Date:(AVES YAYINCILIK, 2001)Bu makalede, bağımsız ve bağımlı gerilim kaynağı tabanlı yeni bir Hücresel Sinir Ağı hücre devresi önerilmiştir. Bu modelde akım kaynaklı Chua ve Yang ‘ın klasik hücre devresinin aksine hücreler için denge noktaları dinamik birimdeki Rx ve Cx’ den bağımsızdırlar. Tam bir hücre devresi tasarlanıp kararlı ve kararsız durumlar için benzetimleri yapılmıstır. Önerilen modelin avantaj ve dezavantajları sonuçlar bölümünde tartışılmıştır.
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Mobile Application Development for the Estimation of Recurrence in Post-Operative Kidney Cancer Cases
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Publisher and Date:(IEEE, 2018)In this paper a post-operative recurrence estimation tool called Sorbellini's nomogram for the kidney cancer patients showing no metastates is introduced and a novel application for mobile devices based on this model is developed for the physician's follow up procedures. The TNM stage tumor size nuclear (Fuhrman) grade the existance of necrosis and vascular invasion are employed as the input parameters for this software to predict the recurrence probability in mentioned patients. Finaly the ...
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Neural Network Design for the Recurrence Prediction of Post-Operative Non-Metastatic Kidney Cancer Patients
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Publisher and Date:(Institute of Electrical and Electronics Engineers Inc., 2016)In this paper various post-operative recurrence estimation models called nomograms for the kidney cancer patients without any metastates are introduced and novel systems based on a Multilayer Perceptron Neural Network are designed to simplify and integrate the mentioned techniques which is believed to ease the physician' s post-operative follow up procedures. The parameters effecting the recurrence are the TNM stage tumor size and nuclear (Fuhrman) grade the existance of necrosis and vascular ...
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Simple and accurate cell macromodels for the simulations of Cellular Neural Networks
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Publisher and Date:(AVES YAYINCILIK, 2002)In this paper, two simple and accurate cell macromodels for PSPICE simulations of Cellular Neural Networks (CNNs) are designed. Firstly, a brief information about CNNs and their benefits are introduced. Then the nonlinear differential equations that characterize the CNNs and the equivalent cell circuit given by Chua and Yang which realizes these equations are presented. With appropriate source transformations, another cell equivalent that employs voltage controlled-voltage sources instead of ...
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Smart Stethoscope
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Publisher and Date:(IEEE, 2020)In this study, a device named smart stethoscope that uses digital sensor technology for sound capture, active acoustics for noise cancellation and artificial intelligence (AI) for diagnosis of heart and lung diseases is developed to help the health workers to make accurate diagnoses. Furthermore, the respiratory diseases are classified by using Deep Learning and Long Short-Term Memory (LSTM) techniques whereas the probability of these diseases are obtained.
