Title
Enhanced Adaptive Volterra Filtering by Automatic Attenuation of Memory Regions and Its Application to Acoustic Echo Cancellation
Abstract
This paper presents a novel scheme for nonlinear acoustic echo cancellation based on adaptive Volterra Filters with linear and quadratic kernels, which automatically prefers those diagonals contributing most to the output of the quadratic kernel with the goal of minimizing the overall mean-square error. In typical echo cancellation scenarios, not all coefficients will be equally relevant for the modeling of the nonlinear echo, but coefficients close to the main diagonal of the second-order kernel will describe most of the nonlinear echo distortions, such that not all diagonals need to be implemented. However, it is difficult to decide the most appropriate number of diagonals a priori, since there are many factors that influence this decision, such as the energy of the nonlinear echo, the shape of the room impulse response, or the step size used for the adaptation of kernel coefficients. Our proposed scheme incorporates adaptive scaling factors that control the influence of each group of adjacent diagonals contributing to the quadratic kernel output. An appropriate selection of these factors serves to emphasize or neglect diagonals of the model as required by the present situation. We provide adaptation rules for these factors based on previous works on combination of adaptive filters, and comprehensive simulations showing the reduced gradient noise reached by the new echo canceller.
Year
DOI
Venue
2013
10.1109/TSP.2013.2251340
IEEE Transactions on Signal Processing
Keywords
Field
DocType
kernel,nonlinear distortion,attenuation,noise,transient response,adaptive filters,nonlinear acoustics
Kernel (linear algebra),Impulse response,Nonlinear system,Control theory,Quadratic equation,Filter (signal processing),Adaptive filter,Mathematics,Gradient noise,Main diagonal
Journal
Volume
Issue
ISSN
61
11
1053-587X
Citations 
PageRank 
References 
12
0.56
9
Authors
5