A PDF-Matched Modification to Stone's Measure of Predictability for Blind Source Separation

نویسندگان

  • Mahdi Khosravy
  • Mohammad Reza Alsharif
  • Katsumi Yamashita
چکیده

This paper presents a PDF-matched modification to Stone’s measure of predictability. The modified measure of predictability is a measure of non-gaussianity too. It is an extent of signal predictability by two different prediction terms. One prediction term is based on a normal gaussian PDF assumption for signal. In contrast, the other one is based on a unit variance supergaussian PDF assumption for signal. By contrastive deployment of the above prediction terms, the modified measure of predictability enables BSS to follow a high kurtosis PDF assumption for signals. As an advantage, not only signals with maximized predictability are recovered, but also with increased non-gaussianity too. Deploying the modified measure of predictability concludes more independent recovered signals. The dominance of BSS based on the modified measure to the previous one has been demonstrated by many tests performed over mixtures of realistic audio signals (music and speech) and over mixtures of gray-scale images.

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

A Gaussianity Measure for Blind Source Separation Insensitive to the Sign of Kurtosis

Various existing criteria to characterize the statistical independence are applied in blind source separation and independent component analysis. However, almost all of them are based on parametric models. The distribution model mismatch between the output PDF (Probability Density Functions) and the chosen underlying distribution model is a serious problem in blind signal processing. Nonparamet...

متن کامل

Blind Source Separation Using Temporal Predictability

A measure of temporal predictability is defined and used to separate linear mixtures of signals. Given any set of statistically independent source signals, it is conjectured here that a linear mixture of those signals has the following property: the temporal predictability of any signal mixture is less than (or equal to) that of any of its component source signals. It is shown that this propert...

متن کامل

Sobre separação cega de fontes: proposições e analise de estrategias para processamento multi-usuario

This thesis is devoted to study blind source separation techniques applied to multiuser processing in digital communications. Using probability density function (pdf) estimation strategies, two multiuser processing methods are proposed. They aim for recovering transmitted signal by using the Kullback-Leibler similarity measure between the signals pdf and a parametric model that contains the sig...

متن کامل

Research of Blind Signals Separation with Genetic Algorithm and Particle Swarm Optimization Based on Mutual Information

Blind source separation technique separates mixed signals blindly without any information on the mixing system. In this paper, we have used two evolutionary algorithms, namely, genetic algorithm and particle swarm optimization for blind source separation. In these techniques a novel fitness function that is based on the mutual information and high order statistics is proposed. In order to evalu...

متن کامل

Novel Quadratic Gaussianity Measures and their Application in Blind Source Separation/Extraction

Various existing criteria to characterize the statistical independence are applied in blind source separation and independent component analysis. However, almost all of them are based on parametric models. The distribution model mismatch between the output PDF (Probability Density Functions) and the chosen underlying distribution model is a serious problem in blind signal processing. Non-parame...

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:

دوره   شماره 

صفحات  -

تاریخ انتشار 2009