Adaptive signal processing
Adaptive filter theory (3rd ed.)
Adaptive filter theory (3rd ed.)
The generalized multidelay adaptive filter: structure andconvergence analysis
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
A stereo echo canceler with correct echo-path identification basedon an input-sliding technique
IEEE Transactions on Signal Processing
EURASIP Journal on Applied Signal Processing
A Spoken Dialog System Speech Interface Based on a Microphone Array
PROPOR '08 Proceedings of the 8th international conference on Computational Processing of the Portuguese Language
Adaptive fractional Fourier domain filtering
Signal Processing
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In unknown environments where we need to identify, model, or track unknown and time-varying channels, adaptive filtering has been proven to be an effective tool. In this contribution, we focus on multichannel algorithms in the frequency domain that are especially well suited for input signals which are not only auto-correlated but also highly cross-correlated among the channels. These properties are particularly important for applications like multichannel acoustic echo cancellation. Most frequency-domain algorithms, as they are well known from the single-channel case, are derived from existing time-domain algorithms and are based on different heuristic strategies, e.g, for stepsize normalization. Here, we present a new rigorous derivation of a whole class of multichannel adaptive filtering algorithms in the frequency domain based on a recursive least-squares criterion. Then, from the normal equation, we derive a generic adaptive algorithm in the frequency domain. Due to the rigorous approach, the proposed framework inherently takes the coherence between all input signal channels into account. An analysis of this multichannel algorithm shows that the mean-squared error convergence is independent of the input signal statistics (i.e., both auto-correlation and cross-correlation). A useful approximation provides interesting links between some well-known algorithms for the single-channel case and the general multichannel framework. We also give design rules for important parameters to optimize the performance in practice. The computational complexity is kept low by introducing several new techniques, such as a robust recursive Kalman gain computation in the frequency domain and efficient fast Fourier transform (FFT) computation tailored to overlapping data blocks. Simulation results and real-time performance for applications such as multichannel acoustic echo cancellation show the high efficiency of the approach.