Fast and accurate methods of independent component analysis: A survey

summary:This paper presents a survey of recent successful algorithms for blind separation of determined instantaneous linear mixtures of independent sources such as natural speech or biomedical signals. These algorithms rely either on non-Gaussianity, nonstationarity, spectral diversity, or on a combination of them. Performance of the algorithms will be demonstrated on separation of a linear instantaneous mixture of audio signals (music, speech) and on artifact removal in electroencephalogram (EEG)

Cram\'er-Rao Bounds for Complex-Valued Independent Component Extraction: Determined and Piecewise Determined Mixing Models

This paper presents Cram\'er-Rao Lower Bound (CRLB) for the complex-valued Blind Source Extraction (BSE) problem based on the assumption that the target signal is independent of the other signals. Two instantaneous mixing models are considered. First, we consider the standard determined mixing model used in Independent Component Analysis (ICA) where the mixing matrix is square and non-singular and the number of the latent sources is the same as that of the observed signals. The CRLB for Independent Component Extraction (ICE) where the mixing matrix is re-parameterized in order to extract only one independent target source is computed. The target source is assumed to be non-Gaussian or non-circular Gaussian while the other signals (background) are circular Gaussian or non-Gaussian. The results confirm some previous observations known for the real domain and bring new results for the complex domain. Also, the CRLB for ICE is shown to coincide with that for ICA when the non-Gaussianity of background is taken into account. %unless the assumed sources' distributions are misspecified. Second, we extend the CRLB analysis to piecewise determined mixing models. Here, the observed signals are assumed to obey the determined mixing model within short blocks where the mixing matrices can be varying from block to block. However, either the mixing vector or the separating vector corresponding to the target source is assumed to be constant across the blocks. The CRLBs for the parameters of these models bring new performance bounds for the BSE problem.Comment: 25 pages, 8 figure

The expression of epidermal growth factor and transforming growth factor-α mRNA in the small intestine of suckling rats: organ culture study

AbstractEpidermal growth factor (EGF) and transforming growth factor-α (TGF-α) are associated with regulation of various gastrointestinal functions. In order to better understand their role in developing small intestine EGF, TGF-α and EGF-R steady-state mRNA levels and transcript stability were determined. Reverse transcription (RT) competitive-polymerase chain reaction (PCR) revealed that intestinal TGF-α mRNA levels were 10-fold higher in comparison with EGF mRNA. The primary intestinal culture technique was used to evaluate mRNA stability. The stability of TGF-α mRNA was remarkably lower than the stability of EGF mRNA. High levels of TGF-α mRNA accompanied by high degradation rate of this mRNA suggested a rapid turnover of intestinal TGF-α mRNA