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Artificial neural network (ANN) and space mapping are recognized as two major recent advances in microwave CAD. ANNs can be trained to learn EM and physics behaviour from component data, and trained ANNs can be used in high-level circuit design. Space mapping has proved to be a breakthrough in engineering optimization allowing expensive EM optimization to be performed effectively with the help of...
Neural networks were inspired by the human brain, with great hopes that neural networks would capture the vast potential of its biological counterpart. This paper explores the link between neural networks and the human brain in the context of simultaneous vs. successive learning. Learning experiments conducted on human subjects were modeled and repeated using neural networks as test subjects. Neural...
Recent development of various domains of artificial intelligence including information retrieval and text/image understanding created demand on new, sophisticated, contextual methods for data analysis. This article formulates neuronal group and extended neuron somatic concepts that can be vastly used in creating such methods. Neural interrelations are described using graphs, construction of which...
In order to avoid the over-fitting in the training of neural networks, we apply Bayesian learning to neural networks. We illustrate the advantages of Bayesian learning by concentrating on multilayer perceptrons (MLP) neural networks and Markov Chain Monte Carlo (MCMC) method for computing the integrations. We conduct the experiments on the foreign exchange rate forecasting by using the approach. The...
CAC-RD (call admission control based on reservation and diagnosis) [1] is call admission control (CAC) for UMTS (universal mobile terrestrial system) 3G networks. It is based on two schemes: channel reservation and network diagnosis. When compared to other CAC mechanisms, CAC-RD can guarantee network availability, reducing priority classes blocking and guarantying some network QoS requirements. Due...
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