Time Domain Recursive Digital Filter Modeling Based on Recurrent Neural Network Training
نویسنده
چکیده
In this paper a time domain recursive digital filter model, based on recurrent neural network is proposed. This problem can be considered as a training procedure of two layer recurrent neural network. The proposed neural network training algorithm is based on determination of the sensitivity coefficients of the recurrent system. The dynamic model of two layer recurrent neural network described by system of recurrent equations is considered. Time domain modeling approach has been applied to design the Nyquist recursive digital filter. Digital filter parameters are obtained by optimization procedure when the requirements to the impulse response in time domain are given.
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