A stable adaptive Hammerstein filter employing partial orthogonalization of the input signals

This paper presents an algorithm that adapts the parameters of a Hammerstein system model. Hammerstein systems are nonlinear systems that contain a static nonlinearity cascaded with a linear system. In this, work, the static nonlinearity is modeled using a polynomial system and the linear filter that follows the nonlinearity is an infinite impulse response system. The adaptation of the nonlinear components is enhanced in the algorithm by orthogonalizing the inputs to the coefficients of the polynomial system. The linear system is implemented as a recursive higher-order filter. The step sizes associated with the recursive components are constrained in such a way as to guarantee bounded-input, bounded-output stability of the overall system. Experimental results included in the paper show that the algorithm performs well and always converges to the global minimum if the input signal is white.