Blind Source Separation Using Temporal Predictability

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...

Blind deconvolution using temporal predictability

A measure of temporal predictability is de-ned, and used for blind deconvolution of sound signals. The method is based on the observation that physical environments act as smoothing -lters, and therefore increase the predictability of signals. These smoothing e0ects can be reversed by a deconvolution -lter which minimises a measure of temporal predictability. This -lter is obtained as the close...

Temporal Models in Blind Source Separation

An EM Method for Spatio-temporal Blind Source Separation Using an AR-MOG Source Model

A maximum likelihood blind source separation algorithm is developed. The temporal dependencies are explained by assuming that each source is an AR process and the distribution of the associated i.i.d. innovations process is described using a Mixture of Gaussians. Unlike most maximum likelihood methods the proposed algorithm takes into account both spatial and temporal information, optimization ...

A Robust Watermarking using Blind Source Separation

In this paper, we present a robust and secure algorithm for watermarking, the watermark is first transformed into the frequency domain using the discrete wavelet transform (DWT). Then the entire DWT coefficient except the LL (Band) discarded, these coefficients are permuted and encrypted by specific mixing. The encrypted coefficients are inserted into the most significant spectral components of...