Blind deconvolution algorithms based on 3rd- and 4th-order cumulants

The authors present three third- and three fourth-order cumulant based algorithms for blind deconvolution and identification of the nonminimum phase (NMP) systems. In the algorithms, based on a noncausal AR (autoregressive) model and a theorem relating to the inverse filter coefficients, the problem of blind deconvolution and identification of a NMP system is reduced to that of solving the corresponding set of linear equations. Thus, the uniqueness of the solution can normally be guaranteed. Furthermore, only the diagonal slices of cumulants are employed in the algorithms, which results in the algorithms being simpler and more accurate. A simulation example is presented for the case of unskewed continuous input, and the feasibility and efficiency of the algorithm are confirmed