Search results for "Blind signal separation"
showing 10 items of 22 documents
Alternative Diagonality Criteria for SOBI
2015
Blind source separation (BSS) is a multivariate data analysis method, whose roots are in the signal processing community. BSS is applied in diverse fields, including, for example, brain imaging and economic time series analysis. In the BSS model there are interesting latent uncorrelated variables, and the aim is to estimate the latent variables from multiple linear combinations of them. In this article we assume that these variables are weakly stationary time series, and we consider estimation methods which are based on approximate joint diagonalization of autocovariance matrices. In the popular SOBI estimator, a set of matrices is most diagonal when the sum of squares of their diagonal ele…
Atrial activity extraction for atrial fibrillation analysis using blind source separation.
2004
This contribution addresses the extraction of atrial activity (AA) from real electrocardiogram (ECG) recordings of atrial fibrillation (AF). We show the appropriateness of independent component analysis (ICA) to tackle this biomedical challenge when regarded as a blind source separation (BSS) problem. ICA is a statistical tool able to reconstruct the unobservable independent sources of bioelectric activity which generate, through instantaneous linear mixing, a measurable set of signals. The three key hypothesis that make ICA applicable in the present scenario are discussed and validated: 1) AA and ventricular activity (VA) are generated by sources of independent bioelectric activity; 2) AA …
Quantifying brain tumor tissue abundance in HR-MAS spectra using non-negative blind source separation techniques
2012
Given high-resolution magic angle spinning (HR-MAS) spectra from several glial tumor subjects, our goal is to differentiate between tumor tissue types by separating the different sources that contribute to the profile of each spectrum. Blind source separation techniques are applied for obtaining characteristic profiles for necrosis, highly cellular tumor and border tumor tissue and providing the contribution (abundance) of each of these tumor tissue types to the profile of each spectrum. The problem is formulated as a non-negative source separation problem. Non-negative matrix factorization, convex analysis of non-negative sources and non-negative independent component analysis methods are …
Non-negative blind source separation techniques for tumor tissue typing using HR-MAS signals.
2010
Given High Resolution Magic Angle Spinning (HR-MAS) signals from several glioblastoma tumor subjects, the goal is to differentiate between tumor tissue types by separating the different sources that contribute to the profile of each spectrum. Blind source separation techniques are applied for obtaining characteristic profiles for necrosis, high cellular tumor and border tumor tissue, and providing the contribution (abundance) of each tumor tissue to the profile of the spectra. The problem is formulated as a non-negative source separation problem. We illustrate the effectiveness of the proposed methods and we analyze to which extent the dimension of the input space could influence the perfor…
Validating rationale of group-level component analysis based on estimating number of sources in EEG through model order selection
2012
This study addresses how to validate the rationale of group component analysis (CA) for blind source separation through estimating the number of sources in each individual EEG dataset via model order selection. Control children, typically reading children with risk for reading disability (RD), and children with RD participated in the experiment. Passive oddball paradigm was used for eliciting mismatch negativity during EEG data collection. Data were cleaned by two digital filters with pass bands of 1-30 Hz and 1-15 Hz and a wavelet filter with the pass band narrower than 1-12 Hz. Three model order selection methods were used to estimate the number of sources in each filtered EEG dataset. Un…
Improving Isolation of Blindly Separated Sources Using Time-Frequency Masking
2008
A refinement technique based on time-frequency masking is proposed to improve source isolation in blind audio source separation algorithms. The refinement technique uses an energy-normalized source-to-interference ratio in order to identify and eliminate interfering energy from the extracted sources. Some examples using this refinement method with different separation algorithms are discussed. The results show that source isolation can be significantly enhanced with negligible degradation of the separated sources.
Simultaneous remote extraction of multiple speech sources and heart beats from secondary speckles pattern
2009
The ability of dynamic extraction of remote sounds is very appealing. In this manuscript we propose an optical approach allowing the extraction and the separation of remote sound sources. The approach is very modular and it does not apply any constraints regarding the relative position of the sound sources and the detection device. The optical setup doing the detection is very simple and versatile. The principle is to observe the movement of the secondary speckle patterns that are generated on top of the target when it is illuminated by a spot of laser beam. Proper adaption of the imaging optics allows following the temporal trajectories of those speckles and extracting the sound signals ou…
Blind source separation based interference suppression schemes for OFDM and DS-CDMA
2015
In statistical wireless signal processing, extraction of unobserved signals from observed mixtures can be achieved using Blind Source Separation (BSS) algorithms. Orthogonal Frequency Division Multiplexing (OFDM) and Direct Sequence-Code Division Multiple Access (DS-CDMA) can be pronounced as the well established predominant air interface communication techniques. Consequences of an effort taken and counteractive solutions to diminish the undesirable influences encountered within the wireless air interface of those techniques with aid of BSS schemes are disclosed. Filter coefficients for the receiver are ascertained with the support of a set of energy functions and the iterative fixed point…
A New Look at Spitzer Primary Transit Observations of the Exoplanet HD 189733b
2014
Blind source separation techniques are used to reanalyse two exoplanetary transit lightcurves of the exoplanet HD189733b recorded with the IR camera IRAC on board the Spitzer Space Telescope at 3.6$\mu$m during the "cold" era. These observations, together with observations at other IR wavelengths, are crucial to characterise the atmosphere of the planet HD189733b. Previous analyses of the same datasets reported discrepant results, hence the necessity of the reanalyses. The method we used here is based on the Independent Component Analysis (ICA) statistical technique, which ensures a high degree of objectivity. The use of ICA to detrend single photometric observations in a self-consistent wa…
Blind multi-user detection by fast fixed point algorithm without prior knowledge of symbol-level timing
2003
We consider the estimation of the source process of the desired user an the downlink of a code-division multiple access (CDMA) communication system. In downlink signal processing, only the code of the mobile telephone user is known, while the codes of the interfering users are unknown. Blind source separation or independent component analysis is an approach offering the solution to this problem. In this work we apply the fast fixed point algorithm to the separation problem. The algorithm is based on fourth-order statistics optimization. Knowledge about the symbol level timing has to be known only coarsely.