Blind deconvolution of non-linear random signals

Presents a new nonparametric blind deconvolution algorithm for colored nonlinear random processes. A blind deconvolution algorithm reconstructs the input of an unknown linear time-invariant (LTI) system having access only to its output. A review of the existing blind deconvolution algorithms reveals that the schemes that require the least amount of knowledge about the input signal and the LTI system, were developed for white input signals, or rely on parametric modeling of both the system and the input. In order to develop nonparametric algorithms for the deconvolution of colored nonlinear processes of unknown statistics, one is forced to consider a two channel approach. The proposed algorithm utilizes the data collected by two different receivers, each being the output of a different system due to the same input. The two systems are then reconstructed combining higher-order statistics of the measured signals and the theory of signal reconstruction from higher-order spectral phase only.