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Linearization of nonlinear systems is a very important topic in many practical applications. The linearization scheme which was suggested in for Volterra systems using adaptive linear and nonlinear FIR filters is considered in this paper. The coefficients of these filters can be recursively estimated using the Least Mean Squares (LMS) algorithm. In this paper, the Recursive Prediction Error Method...
This paper considers the problem of predistortion of nonlinear systems which are described using IIR Hammerstein models by connecting two adaptive IIR Wiener systems. The first adaptive Wiener system is a training filter connected in parallel with the nonlinear system and its coefficients are estimated recursively using the Recursive Prediction Error Method (RPEM) algorithm. The second adaptive Wiener...
This paper considers the problem of predistortion of nonlinear systems which are described using FIR Wiener models by connecting two adaptive FIR Hammerstein systems. The first adaptive Hammerstein system is a training filter connected in parallel with the nonlinear system and its coefficients are estimated recursively using the recursive prediction error method (RPEM) algorithm. The second adaptive...
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