New inverse filter criteria for identification and deconvolution of nonminimum-phase systems by single cumulant slice

The authors propose a family of new cumulant based inverse filter criteria which only require a single slice of cumulants of the inverse filter output for the identification and deconvolution of linear time-invariant (LTI) nonminimum-phase systems with only non-Gaussian output measurements contaminated by Gaussian noise. Some simulation results and an application to speech deconvolution are provided to demonstrate that inverse filtering algorithms based on the proposed new criteria work well.