Blind source-separation using second-order cyclostationary statistics
نویسندگان
چکیده
This paper studies the blind source separation (BSS) problem with the assumption that the source signals are cyclostationary. Identifiability and separability criteria based on second-order cyclostationary statistics (SOCS) alone are derived. The identifiability condition is used to define an appropriate contrast function. An iterative algorithm (ATH2) is derived to minimize this contrast function. This algorithm separates the sources even when they do not have distinct cycle frequencies.
منابع مشابه
References in Blind Separtion & Identification, and Control Theory
A linear prediction-like algorithm for passive localization of near-field sources, [5] K. Abed Meraim and Y. Hua, " Blind identification of multi-input multi-output system using minimum noise subspace, " IEEE Trans. On subspace methods for blind identification of single-input multiple-output FIR systems, " IEEE Trans. Blind source separation using second order cyclostationary statistics, " IEEE...
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ورودعنوان ژورنال:
- IEEE Trans. Signal Processing
دوره 49 شماره
صفحات -
تاریخ انتشار 2001