Algorithms for identifying clusters of near-common zeros in multichannel blind system identification and equalization

Blind system identification (BSI) and equalization algorithms have been applied to multichannel systems with high order such as found in acoustic impulse responses. Studies on the performance of such algorithms in the presence of near-common zeros have been limited to low order systems. In this work, we propose two high order clustering algorithms which efficiently extract clusters of near-common zeros within a specified pairwise distance in the z-plane. Using these algorithms, we then quantify the number of common zeros that exist in acoustic systems. In addition, we show how these algorithms can be applied to study of BSI and equalization algorithms in the presence of near-common zeros for such acoustic systems.