A nonlinear pre-filtering technique for set-theoretic linear blind deconvolution scheme

Recently, a novel set-theoretic linear blind deconvolution scheme was developed by applying hybrid steepest descent method to Kundur and Hatzinakos´ simple a priori information on the original object, where the performance of the scheme seems relatively sensitive to the additive measurement noise. In this paper, we remark some well-known nonlinear filtering techniques which realize immediate effect to suppress the influence of the additive measurement noise in the input to the scheme. Numerical examples show ϵ-separating nonlinear pre-filtering techniques work suitably to this noisy blind deconvolution problem.