engleski

Identification of nonlinear dynamic systems using dynamic neural network

An attempt has been made to establish a nonlinear dynamic discrete-time neuron model. This dynamic discrete-time neuron disposes of local memory, in that it has dynamic states. Based on such neuron, a Dynamic Multi Layer Perceptron Neural Network is proposed for the identification of a dynamic discrete-time nonlinear system. To accelerate the convergence of proposed extended dynamic error back propagation learning algorithm, the momentum method is applied. The learning results are presented in terms that are insensitive to the learning data range and allow easy comparison with other learning algorithms, independent of machine architecture or simulator implementation.

identification; nonlinear dynamic system; dynamic neural network

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