Now showing items 1-5 of 5

  • A numerical method for frequency determination in the astable cellular neural networks with opposite-sign templates 

    Authors:Özmen, Atilla; Tander, Baran
    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 ...

  • Amplitude and Frequency Modulations with Cellular Neural Networks 

    Authors:Tander, Baran; Özmen, Atilla
    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 ...

  • Channel Equalization with Cellular Neural Networks 

    Authors:Özmen, Atilla; Tander, Baran
    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) ...

  • Mobile Application Development for the Estimation of Recurrence in Post-Operative Kidney Cancer Cases 

    Authors:Tander, Baran; Özmen, Atilla; Ozden, Ender
    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 ...

  • Neural Network Design for the Recurrence Prediction of Post-Operative Non-Metastatic Kidney Cancer Patients 

    Authors:Tander, Baran; Özmen, Atilla; Ozden, Ender
    Publisher and Date:(IEEE, 2015)
    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 ...