Identification of systems using radial basis networks feedbacked with FIR filters
A new model of a radial basis neural network is presented in this article which is fedbacked with a FIR filter. Using various neurons of this type, it is possible to construct a recurrent neural network, where the coefficients of each filter and the synaptic connections are adjusted to minimize an error function. The simulations carried out show the validity of this method for identifying systems with memory.
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