Using the Pearson correlation coefficient to develop an optimally weighted cross relation based blind SIMO identification algorithm
Yiteng Arden Huang, Jacob Benesty, Jingdong Chen · 2009
Blind SIMO identification is challenging when additive noise is strong and for ill-conditioned/acoustic SIMO systems. A weighted cross relation (CR) algorithm presumably can be robust to noise but there lacks a practical way to define the weights. In this paper, the Pearson correlation coefficient (PCC) is used to develop an optimally weighted CR algorithm, which is validated by simulations.