Earticle

초록

영어

This paper addresses the problem of independent component extraction of complex-valued signals in convolutive mixtures. Most previous research focused on real-valued convolutive ICA, and corresponding solution methods are generally computationally complex and inefficient for real application. In order to solve the problem, we propose a novel method based on first-order statistics, which includes several single-step and iterative separators to satisfy different demands of engineering applications. We also provided the theoretical performance analysis, which is validated by experimental simulations. It is observed from the simulations that various factors (especially the noncircularity) affect the extraction performance of separators; hence we offer some advice on how to choose separators properly. Besides, the proposed iterative separators generally perform better and converge faster compared to two complex FastICA algorithms.

목차

Abstract
 1. Introduction
 2. Problem Statement
  2.1. Complex Preliminaries
  2.2. Complex ICA in the Convolutive Mixture Model
 3. Algorithm Development
 4. Performance Analysis
  4.1. Theoretical Performance in Terms of ISR
  4.2. Theoretical Performance Concerning Iterative Separators
 5. Simulation Results and Discussion
  5.1. Performance of Single-step Algorithms
  5.2. Performance of Iterative Algorithms
 6. Conclusion
 References

키워드

저자

• Peng-cheng Xu [ College of Communications Engineering, PLA University of Science and Technology, Haifu Xiang 1, Guanghua Road, 210007, Nanjing, P.R. China ]
• Yue-hong Shen [ College of Communications Engineering, PLA University of Science and Technology, Haifu Xiang 1, Guanghua Road, 210007, Nanjing, P.R. China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Signal Processing, Image Processing and Pattern Recognition

• 간기

  격월간

• pISSN

  2005-4254

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605