Semiparametric Approach to Multichannel Blind Deconvolution of Nonminimum Phase Systems
Liqing Zhang, Шун-ичи Амари, Andrzej S Cichocki · 1999
In this paper we discuss the semiparametric statistical model for blind deconvolution. First we introduce a Lie Group to the manifold of noncausal FIR filters. Then blind deconvolution problem is formulated in the framework of a semiparametric model, and a family of estimating functions is derived for blind deconvolution. A natural gradient learning algorithm is developed for training noncausal filters. Stability of the natural gradient algorithm is also analyzed in this framework. 1 Introduction Recently blind separation/deconvolution has been recognized as an increasing important research area due to its rapidly growing applications in various fields, such as telecommunication systems, image enhancement and biomedical signal processing. Refer to review papers [7] and [13] for details. A semiparametric statistical model treats a family of probability distributions specified by a finite-dimensional parameter of interest and an infinite-dimensional nuisance parameter [12]. Amari...