A Study on Robust Series-Parallel Adaptive Filter for Near-End Noise

Abstract

In this paper, we propose a robust series-parallel adaptive filter for near-end noise. The compensating method of the bias error when the near-end noise can be assumed to a white signal is known well. The example of representative adaptive algorithm is that the weights are controlled under the unit norm condition. We considered the adaptive filter that was able to be applied when the near-end noise is a colored signal. The cost function is a square-sum of the cross-correlation coefficient of the input signal and the estimation error. The analytical results and the above mentioned feature are strictly verified by computer simulation.