Nonlinear System Identification Using a Subband Adaptive Volterra Filter

This paper proposes a flexible and efficient subband adaptive second order Volterra filter structure for nonlinear system identification. Acoustic echo cancellation is an application of system identification that is critical in hands-free telephony, for which a linear model is usually assumed. However, echo cancellation is limited by inherent system nonlinearities, of which loudspeaker distortion is one of the main sources. Experimental results, obtained in an office room environment, show that the proposed structure was able to model the nonlinear room transfer function more accurately than a linear only model by up to 10 dB lower mean square error, at a comparable computational complexity.