Blind deconvolution in nonminimum phase systems using cascade structure

  • Authors:
  • Bin Xia;Liqing Zhang

  • Affiliations:
  • Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China;Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, China

  • Venue:
  • EURASIP Journal on Applied Signal Processing
  • Year:
  • 2007

Quantified Score

Hi-index 0.00

Visualization

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.