Now showing items 1-3 of 3

  • 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 ...

  • Bayesian estimation of discrete-time cellular neural network coefficients 

    A new method for finding the network coefficients of a discrete-time cellular neural network (DTCNN) is proposed. This new method uses a probabilistic approach that itself uses Bayesian learning to estimate the network coefficients. A posterior probability density function (PDF) is composed using the likelihood and prior PDFs derived from the system model and prior information respectively. This posterior PDF is used to draw samples with the help of the Metropolis algorithm a special case of the ...

  • Bayesian estimation of discrete-time cellular neural network coefficients 

    Authors:Özer, Hakan Metin; Özmen, Atilla; Şenol, Habib
    Publisher and Date:(Tübitak, 2017)
    A new method for finding the network coefficients of a discrete-time cellular neural network (DTCNN) is proposed. This new method uses a probabilistic approach that itself uses Bayesian learning to estimate the network coefficients. A posterior probability density function (PDF) is composed using the likelihood and prior PDFs derived from the system model and prior information, respectively. This posterior PDF is used to draw samples with the help of the Metropolis algorithm, a special case ...