For speech applications, blind source separation provides an efficient strategy to enhance the target signal and to reduce the background noise in a noisy environment. Most ICA-based blind source separation (BSS) algorithms are designed under the assumption that the target and interfering signals are spatially located. When the number of interfering signals is small, one of the BSS outputs is e...

Without any information on the mixing system, the blind source separation (BSS) technique efficiently separates mixed signals. The approach called evolutionary algorithms was used for the BSS problem in this paper. The fitness function based on the feature distance and kurtosis was proposed to measure the degree of the separated signals in this paper. Compared with the traditional algorithm in ...

We propose a combination of blind source separation (BSS) and independent component analysis (ICA) (signal decomposition into artifacts and nonartifacts) with support vector machines (SVMs) (automatic classification) that are designed for online usage. In order to select a suitable BSS/ICA method, three ICA algorithms (JADE, Infomax, and FastICA) and one BSS algorithm (AMUSE) are evaluated to d...

The analysis and characterization of atrial tachyarrhythmias requires the previous estimation of the atrial activity (AA) free from any ventricular activity and other artefacts. This contribution considers a blind source separation (BSS) model to separate the AA from multilead electrocardiograms (ECGs). Previously proposed BSS methods for AA extraction exploit only the spatial diversity introdu...

Blind Source Separation (BSS) is a challenging matrix factorization problem that plays a central role in multichannel imaging science. In a large number of applications, such as astrophysics, current unmixing methods are limited since real-world mixtures are generally affected by extra instrumental effects like blurring. Therefore, BSS has to be solved jointly with a deconvolution problem, whic...

There is a great interest to apply BSS methods in mechanical system signal processing for monitoring or diagnosis purpose. Actually, we show that BSS allows to recover the vibratory information issued from a single rotating machine working in a noisy environment by freeing the sensor signal from the contribution of other working machines. In that way, BSS can be used as a pre-processing step to...

Cellular networks are now rapidly evolving to the renewable heterogeneous network (HetNet) architectures, where a mixture of macro base stations (BSs) and small cell BSs coexist. Particularly, these BSs are partly-powered or self-powered by renewable energy sources (RES). In this context, joint user association and resource allocation is challenging. In addition, wireless backhaul is rapidly be...

Despite several recent proposals to achieve Blind Source Separation (BSS) for realistic acoustic signals, the separation performance is still not enough. In particular, when the length of an impulse response is long, the performance is highly limited. In this paper, we consider the reason for the poor performance of BSS in a long reverberation environment. First, we show that it is useless to b...

We propose a time-domain BSS algorithm that utilizes geometric information such as sensor positions and assumed locations of sources. The algorithm tackles the problem of convolved mixtures by explicitly exploiting the non-stationarity of the acoustic sources. The learning rule is based on secondorder statistics and is derived by natural gradient minimization. The proposed initialization of the...

BACKGROUND Tobacco use is responsible for a large proportion of the total disease burden from tuberculosis. Pakistan is one of the 10 high-burden countries for both tuberculosis and tobacco use. OBJECTIVE To assess the effectiveness of a behavioral support intervention and bupropion in achieving 6-month continuous abstinence in adult smokers with suspected pulmonary tuberculosis. DESIGN Clu...