Adaptive filter theory
System identification: theory for the user
System identification: theory for the user
Signal Processing
Multirate systems and filter banks
Multirate systems and filter banks
Adaptation of a memoryless preprocessor for nonlinear acoustic echo cancelling
Signal Processing - Special issue on current topics in adaptive filtering for hands-free acoustic communication and beyond
Time series: data analysis and theory
Time series: data analysis and theory
Orthogonalized power filters for nonlinear acoustic echo cancellation
Signal Processing
Nonlinear acoustic echo cancellation with 2nd order adaptive Volterra filters
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Adaptive nonlinear system identification in the short-time fourier transform domain
IEEE Transactions on Signal Processing
Modeling and identification of nonlinear systems in the short-time fourier transform domain
IEEE Transactions on Signal Processing
Parallel-cascade realizations and approximations of truncatedVolterra systems
IEEE Transactions on Signal Processing
Efficient algorithms for Volterra system identification
IEEE Transactions on Signal Processing
A blind approach to Hammerstein model identification
IEEE Transactions on Signal Processing
Penalized least squares estimation of Volterra filters and higherorder statistics
IEEE Transactions on Signal Processing
Performance analysis of the deficient length LMS adaptive algorithm
IEEE Transactions on Signal Processing - Part I
An LMS style variable tap-length algorithm for structure adaptation
IEEE Transactions on Signal Processing
A new approach to subband adaptive filtering
IEEE Transactions on Signal Processing
System Identification in the Short-Time Fourier Transform Domain With Crossband Filtering
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Audio, Speech, and Language Processing
Quantifying the accuracy of Hammerstein model estimation
Automatica (Journal of IFAC)
Identification of linear systems with nonlinear distortions
Automatica (Journal of IFAC)
Adaptive nonlinear system identification in the short-time fourier transform domain
IEEE Transactions on Signal Processing
Modeling and identification of nonlinear systems in the short-time fourier transform domain
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
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In this paper, we introduce an adaptive algorithm for nonlinear system identification in the short-time Fourier transform (STFT) domain. The adaptive scheme consists of a parallel combination of a linear component, represented by crossband filters between subbands, and a quadratic component, which is modeled by multiplicative cross-terms. We adaptively update the model parameters using the least-mean-square (LMS) algorithm, and derive explicit expressions for the transient and steady-state mean-square error (mse) in frequency bins for white Gaussian inputs. We show that estimation of the nonlinear component improves the mse performance only when the power ratio of nonlinear to linear components is relatively high. Furthermore, as the number of crossband filters increases, a lower steady-state mse may be obtained at the expense of slower convergence. Experimental results support the theoretical derivations.