Nonlinear System Identification Using Exponential Swept-Sine Signal

Antonin Novak (1) , Laurent Simon (1) , F. Kadlec (2) , P. Lotton (1)

1 LAUM - Laboratoire d'Acoustique de l'Université du Mans
2 Multimedia Group

In this paper, we propose a method for nonlinear system (NLS) identification using a swept-sine input signal and based on nonlinear convolution. The method uses a nonlinear model, the non-parametric generalized polynomial Hammerstein model made of power series associated with linear filters. Simulation results show that the method identifies the nonlinear model of the system under test and estimates the linear filters of the unknown NLS. The method has been also tested on a real-world system: an audio limiter. Once the nonlinear model of the limiter is identified, a test signal can be regenerated to compare the outputs of both the real-world system and its nonlinear model. The results show good agreement between both model-based and real-world system outputs.

Domaines: Sciences de l'ingénieur [physics]

Antonin Novak, Laurent Simon, F. Kadlec, P. Lotton. Nonlinear System Identification Using Exponential Swept-Sine Signal. IEEE Transactions on Instrumentation and Measurement, 2010, 59 (8), pp.2220-2229. ⟨10.1109/TIM.2009.2031836⟩. ⟨hal-02504286⟩