Maximization of statistical moments for blind separation of sources revisited

نویسندگان

  • Susana Hornillo-Mellado
  • Rubén Martín-Clemente
  • Carlos García Puntonet
  • José I. Acha
  • Juan Manuel Górriz
چکیده

In this paper we revisit a classic HOS-based BSS criterion, namely the maximization of the higher-order moments of the estimated sources. The main contributions of this paper are: (i) a thorough study of the solutions given by popular HOS-based BSS criteria (including spurious solutions) and (ii) a method for estimating the source signals based on the eigendecomposition of certain adjustable HOS-matrices. Results are illustrated by computer simulations. r 2006 Elsevier B.V. All rights reserved.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

An EM Algorithm for Independent Component Analysis in the Presence of Gaussian Noise

Abstract—An expectation-maximization (EM) algorithm for independent component analysis in the presence of gaussian noise is presented. The estimation of the conditional moments of the source posterior can be accomplished by maximum a posteriori estimation. The approximate conditional moments enable the development of an EM algorithm for inferring the most probable sources and learning the param...

متن کامل

Fast ICA for noisy data using Gaussian moments

A novel approach for the problem of estimating the data model of independent component analysis (or blind source separation) in the presence of gaussian noise is introduced. We de ne the gaussian moments of a random variable as the expectations of the gaussian function (and some related functions) with di erent scale parameters, and show how the gaussian moments of a random variable can be esti...

متن کامل

Discriminacy of the minimum range approach to blind separation of bounded sources

The Blind Source Separation (BSS) problem is often solved by maximizing objective functions reflecting the statistical dependency between outputs. Since global maximization may be difficult without exhaustive search, criteria for which it can be proved that all the local maxima correspond to an acceptable solution of the BSS problem have been developed. These criteria are used in a deflation pr...

متن کامل

Alternative Statistical Gaussianity Measure Using the Cumulative Density Function

This paper discusses a novel method called ‘ICA with OS’ (‘Independent Component Analysis with Order Statistics’) to solve the vital problem of Blind Source Separation. The key of the procedure is a new alternative Gaussianity measure estimated by Order Statistics of the cdf (cumulative density function) instead of the common pdf (probability density function) moments. The maximization of this ...

متن کامل

Feature Extraction Approach to Blind Source Separation

Local independent component analysis is formulated as a task involving the extraction of local geometric structure in the joint distribution. Because the geometrical structure of statistical independence is not well captured by statistical descriptions such as moments and cumulants, we use feature detection tools from image analysis to locate the local independent component coordinate system. T...

متن کامل

ذخیره 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 نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Neurocomputing

دوره 69  شماره 

صفحات  -

تاریخ انتشار 2006