원문정보
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
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