A noise-robust dual filter approach to multichannel blind system identification

We present a novel frequency domain blind multichannel identification approach. This is a dual filter based approach comprising a background and a foreground filter. The foreground filter tracks the changes in the cost function of the background filter and employs an update decision criterion making it robust to observation noise and facilitating tracking of changes in the unknown system. Simulation results for both speech and white Gaussian noise input signals are presented to illustrate the algorithm's performance for acoustic systems.