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Recurrent neural networks are represented as non-linear models of dynamic systems. This kind of neural networks is divided into two groups, which are globally and locally recurrent neural networks. Some types are distinguished among globally recurrent networks. The major approximation properties and features of every distinguished type are emphasized. The represented analysis is useful for choosing...
Using the adequate number of Multilayer Perceptron input, hidden and output layers, the Cellular Neural Network dynamic behavior, when the system converges to a fixed-point, can be reproduced by a Multilayer Perceptron with restrictions. A Multilayer Perceptron can then be defined in order to act as a two neuron Cellular Neural Network and vice-versa. From this, we combine their properties in order...
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