Modeling and adaptive filtering of systems with hysteresis nonlinearities

The technique introduces a model that can be used effectively for system identification and modeling. The technique includes an order of memory within a nonlinearity element for modeling of hysteresis effects. The nonlinear channel is divided into a memory nonlinearity followed by a dispersive linear system. Assuming that the dispersive linear system is stationary during initialization and the nonlinearity does not change while the dispersive linear system varies with time, the quantized mean field annealing algorithm is applied to obtain the coefficients and the order of the memory of the nonlinearity, and a conventional recursive least squares fast transversal filter (RLS/FTF) is applied to determine the weights of the dispersive linear system. The application of this method to a full duplex digital subscriber loop, is discussed. Significant performance improvements were achieved