Blind source separation by nonstationarity of variance: a cumulant-based approach
نویسنده
چکیده
Blind separation of source signals usually relies either on the nonGaussianity of the signals or on their linear autocorrelations. A third approach was introduced by Matsuoka et al. (1995), who showed that source separation can be performed by using the nonstationarity of the signals, in particular the nonstationarity of their variances. In this paper, we show how to interpret the nonstationarity due to a smoothly changing variance in terms of higher order cross-cumulants. This is based on the time-correlation of the squares (energies) of the signals and leads to a simple optimization criterion. Using this criterion, we construct a fixed-point algorithm that is computationally very efficient.
منابع مشابه
A Fast Algorithm for Blind Separation of Complex Valued Signals with Nonlinear Autocorrelation
—Blind source separation of complex valued signals has been a hot issue especially in the field of multi-input/multi-output (MIMO) digital communications. Many contrast functions based on the nonlinear structure of the signals have been proposed to extract the unknown sources. However, these researches usually focused on the real-valued case, but ignoring the complex problem. This paper propos...
متن کاملA Double Referenced Contrast for Blind Source Separation
This paper addresses the problem of blind source separation (BSS). To recover original signals, from linear instantaneous mixtures, we propose a new contrast function based on the use of a double referenced system. Our approach assumes statistical independence sources. The reference vectors will be incrusted in the cumulant to evaluate the independence. The estimation of the separating matrix w...
متن کاملEigendecomposition of self-tuned cumulant-matrices for blind source separation
Existing algorithms for blind source separation are often based on the eigendecomposition of fourth-order cumulant matrices. However, when the cumulant matrices have close eigenvalues, their eigenvectors are very sensitive to errors in the estimation of the matrices. In this paper, we show how to produce a cumulant matrix that has a well-separated extremal eigenvalue. The corresponding eigenvec...
متن کاملInstantaneous blind source separation based on the exploitation of temporal correlations and nonstationarity
This paper provides insight into the algebraic and geometric structure of Instantaneous Blind Signal Separation based on the assumptions that the cross-correlation functions of the source signals are zero and that the source auto-correlation functions are linearly independent. The presented viewpoint is unifying in the sense that all kinds of statistical variability in the data, such as tempora...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید
ثبت ناماگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید
ورودعنوان ژورنال:
- IEEE transactions on neural networks
دوره 12 6 شماره
صفحات -
تاریخ انتشار 2001