“…JD algorithms can be classified in orthogonal JD (OJD) methods which proceed in two steps: whitening and orthogonal diagonalization steps, and non orthogonal JD methods which avoid the whitening step and help improve the separation performance when applied in BSS [3]. In this paper, we provide a comparative performance analysis of major iterative CNOJD algorithms, namely: ACDC (Alternating Columns and Diagonal Centring) developed by Yeredor in 2002 [4], FAJD (Fast Approximative Joint diagonalization Algorithm) developed by Li and Zhang in 2007 [5], UWEDGE (UnWeighted Exhaustive Diagonalization using Gauss itErations) developed by Tichavsky and Yeredor in 2008 [6], JUST (Joint Unitary Shear Transformation) developed by Iferroudjene, Belouchrani and Abed-Meraim in 2009 [7], CVFFdiag (Complex Valued Fast Frobenius diagonalization) developed by Xu, Feng and Zheng in 2011 [8], LUCJD (LU decomposition for Complex Joint Diagonalization) developed by Wang, Gong and Lin in 2012 [9] and CJDi (Complex Joint Diagonalization) developed by Mesloub, AbedMeraim and Belouchrani in 2012 [10]. Note that we restrict our comparative study only to iterative methods and we exclude the non iterative methods [11] [12] which are of higher complexity order especially for large dimensional systems.…”