Blind Source Separation with Outliers in Transformed Domains

Blind wideband source separation

This paper deals with the general problem of separating two independent wideband sources when they are mixed by unknown filters. In order to solve this problem. a backward framework is proposed which is composed of two different stages. The fiist one consists of two linear predictors devoted to improve the source separation, whitening the input signals. Their coefficients are calculated applyin...

Advances in Blind Source Separation

Blind source separation (BSS) and related topics such as independent component analysis (ICA), sparse component analysis (SCA), or nonnegative matrix factorization (NMF) have become emerging tools inmultivariate signal processing and data analysis and are now one of the hottest and emerging areas in signal processing with solid theoretical foundations and many potential applications. In fact, B...

Prewhitened Blind Source Separation with Orthogonality

Blind Source Separation with Pure Delay Mixtures

We address the problem of blind separation of mixtures consisting of pure unknown delays in addition to scalar mixing coefficients. Such a mixture is a hybrid situation resembling both static and convolutive mixtures, but essentially different from both: On one hand, static-mixture approaches cannot be readily applied in this context; On the other hand, conventional convolutive-mixture approach...

Transform domain steganography with blind source separation

This paper applies blind source separation or independent component analysis for images that may contain mixtures of text, audio, or other images for steganography purposes. The paper focuses on separating mixtures in the transform domain such as Fourier domain or the Wavelet domain. The study addresses the effectiveness of steganography when using linear mixtures of multimedia components and t...