From Acoustic Nonlinearity to Adaptive Nonlinear System Identification

Audio and acoustic signal processing predominantly relies on the theory of linear systems. The existence of nonlinearity in real systems is recognized since long though. Numerous criteria are available to assess the degree of nonlinearity. Explicit nonlinear signal processing with tangible structure and relevant performance, however, still appears rarely. In this paper, we focus on the memoryless Hammerstein-type of nonlinearity which is useful to characterize applications of speech and audio reproduction such as, e.g., hands-free systems with loudspeaker distortion. The goal of the paper is to point to some recent research on adaptive nonlinear system identification and to put it into perspective with established concepts and criteria in the nonlinear domain.