WDM monitoring technique using adaptive blind signal separation
نویسندگان
چکیده
منابع مشابه
Blind Signal Separation Using an Extended Infomax Algorithm
The Infomax algorithm is a popular method in blind source separation problem. In this article an extension of the Infomax algorithm is proposed that is able to separate mixed signals with any sub- or super-Gaussian distributions. This ability is the results of using two different nonlinear functions and new coefficients in the learning rule. In this paper we show how we can use the distribution...
متن کاملBlind Signal Separation Using an Extended Infomax Algorithm
The Infomax algorithm is a popular method in blind source separation problem. In this article an extension of the Infomax algorithm is proposed that is able to separate mixed signals with any sub- or super-Gaussian distributions. This ability is the results of using two different nonlinear functions and new coefficients in the learning rule. In this paper we show how we can use the distribution...
متن کاملWDM monitoring through blind signal separation based on higher-order statistics
Abstract: WDM transmission performance can be monitored efficiently by blind signal separation methods based on higher-order statistics for WDM-channel extraction. Relative to a recent method, our procedure has reduced complexity, no stability problems, and better performance. c © 2002 Optical Society of America OCIS codes: (060.4510) Optical communications; (070.6020) Signal processing; (070.6...
متن کاملAdaptive Blind Signal Separation Using a New Simplified Mixing Model
This paper addresses the problem of separating multiple speakers from mixtures of these that are obtained using multiple microphones in a room. A new adaptive blind separation algorithm is proposed which is based on a new simplified mixing model and uses only second order statistics. The simplified model uses the fact that the acoustic transfer functions from a single source to two closely spac...
متن کاملBlind signal separation using an adaptive weibull distribution
We propose an independent component analysis (ICA) algorithm which can separate mixtures of suband superGaussian source signals with self-adaptive nonlinearities. The ICA algorithem in the framework of natural Riemannian gradient is derived using the parameterized Weibull density model. The nonlinear function in ICA algorithem is self-adaptive and is controlled by the shape parameter of Weibull...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: IEEE Photonics Technology Letters
سال: 2001
ISSN: 1041-1135,1941-0174
DOI: 10.1109/68.914336