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Amplitude and Frequency Modulations with Cellular Neural Networks
(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 ...
Correlation of ternary liquid--liquid equilibrium data using neural network-based activity coefficient model
(Springer, 2014)
Liquid--liquid equilibrium (LLE) data are important in chemical industry for the design of separation equipments and it is troublesome to determine experimentally. In this paper a new method for correlation of ternary LLE ...
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 ...
Channel Equalization with Cellular Neural Networks
(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 ...
Correlation of Experimental Liquid-Liquid Equilibrium Data for Ternary Systems Using NRTL and GMDH-Type Neural Network
(Amer Chemical Soc, 2017)
In this work liquid liquid equilibrium (LLE) data for the ternary systems (water + propionic acid + solvent) were experimentally obtained at atmospheric pressure and 298.2 K. The ternary systems show type-1 behavior of ...
Neural Network Design for the Recurrence Prediction of Post-Operative Non-Metastatic Kidney Cancer Patients
(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 ...
Realization of ideal filter characteristics via genetic algorithm
(2011)
In this paper realization of ideal filter characteristics via genetic algorithm has been studied. The filter is defined as a lossless two-port terminated normalized source and load resistances and the coefficients of its ...
Design and implementation of a negative feedback oscillator circuit based on a Cellular Neural Network with an Opposite Sign Template
(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 ...
Genetic algorithm based broadband equalizer design with ripple level control
(IEEE, 2012)
In this paper broadband equalizer design with ripple control via genetic algorithm has been studied. The equalizer is defined as a lossless two-port terminated by load impedance and the coefficients of its describing ...
Detection of Trojans in integrated circuits
(IEEE, 2012)
This paper presents several signal processing approaches in Trojan detection problem in very large scale integrated circuits. Specifically wavelet transforms spectrograms and neural networks are used to analyze power ...