An adaptive solution for nonlinear system identification

This paper proposes a new and very simple method to perform identification of nonlinearities in systems that are supposed to be linear. The improvement with respect to the previous approaches lies in the low computational complexity of the solution and the convenient possibility of online evaluation. Simulation results show that the proposed method provides good performance in terms of coefficients identification, resulting in both low steady-state error and high convergence rate of the algorithm, which justifies its applicability in practice.