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Blind Deconvolution in Nonminimum Phase Systems Using Cascade Structure

Open Access
Research Article
Part of the following topical collections:
  1. Advances in Blind Source Separation

Abstract

We introduce a novel cascade demixing structure for multichannel blind deconvolution in nonminimum phase systems. To simplify the learning process, we decompose the demixing model into a causal finite impulse response (FIR) filter and an anticausal scalar FIR filter. A permutable cascade structure is constructed by two subfilters. After discussing geometrical structure of FIR filter manifold, we develop the natural gradient algorithms for both FIR subfilters. Furthermore, we derive the stability conditions of algorithms using the permutable characteristic of the cascade structure. Finally, computer simulations are provided to show good learning performance of the proposed method.

Keywords

Manifold Computer Simulation Learning Process Deconvolution Quantum Information 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Xia and Zhang 2007

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringShanghai Jiao Tong UniversityShanghaiChina

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