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Bayesian estimation of discrete-time cellular neural network coefficients
(TUBITAK Scientific & Technical Research Council Turkey, 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 ...
Artificial neural network based estimation of sparse multipath channels in OFDM systems
(SPRINGER, VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS, 2021-01)
In order to increase the transceiver performance in frequency selective fading channel environment, orthogonal frequency division multiplexing (OFDM) system is used to combat inter-symbol-interference. In this work, a ...