Universal approximation using radial-basis-function networks
Neural Computation
Approximation and radial-basis-function networks
Neural Computation
Static and Dynamic Neural Networks: From Fundamentals to Advanced Theory
Static and Dynamic Neural Networks: From Fundamentals to Advanced Theory
Networks and the Best Approximation Property
Networks and the Best Approximation Property
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This paper considers the joint application of neural networks and antenna array systems in mobile, satellite and sensor systems. The main assumption is that there is a possibility of a large number of neurons in the network according the fact that the human brain uses a huge number of neurons. Results of detail analyze for signal detection, direction of arrival estimation, and beamforming are presented. First signal detection is performed with PNN neural network than with RBE, and systems are compared. Then DOA estimation and beamforming are presented for both neural networks. Results from computer simulations show the ability of these systems to give satisfactory performances although limitations are noted. Overall analyze gives a high contribution in finding an optimal future neuro-antenna array systems as very elegant, cost effective and efficient solution for telecommunication systems.