Renyi’s entropy can be used as a cost function for blind source separation (BSS). Previous works have emphasized the advantage of setting Renyi’s exponent to a value different from one in the context of BSS. In this paper, we focus on zero-order Renyi’s entropy minimization for the blind extraction of bounded sources (BEBS). We point out the advantage of choosing the extended zero-order Renyi’s...

In this paper we consider blind interference mitigation in direct sequence spread spectrum communication system under intentional jamming. Recent work [1] presents a general framework in which blind source separation (BSS) techniques are utilized to enhance conventional detection. However, only second order statistics were utilized which makes the scheme vulnerable to temporally uncorrelated in...

We present a prototype system for real-time blind source separation (BSS) and directions of arrival (DOA) estimation. Our system uses a small three-dimensional array with 8 microphones and has the ability to separate signals distributed in threedimensional space. The mixed signals observed by the microphone array are processed by Independent Component Analysis (ICA) in the frequency domain. The...

The blind source separation (BSS) problem is often solved by maximizing objective functions reflecting the statistical independence between outputs. Since global maximization may be difficult without exhaustive search, criteria for which all the local maxima correspond to an acceptable solution of the BSS problem are of interest. It is known that some BSS criteria used in a deflation procedure ...

This paper presents a novel scheme for detection of watermarks embedded in multimedia signals using spread spectrum (SS) techniques. The detection method is centered on using the model that the embedded watermark and the host signal are mutually independent. The proposed detector assumes that the host signal and the watermark obey non-Gaussian distributions. The proposed blind watermark detecto...

Blind methods are powerful tools when very weak information is necessary. Although many algorithms can be called blind, in this paper, we focus on blind source separation (BSS) and independent component analysis (ICA). After a discussion concerning the blind nature of these techniques, we review three main points: the separability, the criteria, the algorithms.

This paper presents a novel blind watermark detection/decoding scheme for spread spectrum (SS) based watermarking exploiting the fact that the embedded watermark and the host signal are mutually independent. The proposed detector assumes that the host signal and the watermark obey non-Gaussian distributions. The proposed scheme employs the theory of blind source separation (BSS) using independe...

This paper proposes hands-free speech recognition using blind source separation (BSS) post-processed by two-stage spectral subtraction (2S-SS). The BSS using independent component analysis (ICA) estimates a target signal and jammer signals. The 2S-SS removes its residual crosstalk components and suppresses spatially-distributed noise not separated by BSS. In large vocabulary continuous speech r...

Over the last ten years blind source separation (BSS) has become a prominent processing tool in the study of human electroencephalography (EEG). Without relying on head modeling BSS aims at estimating both the waveform and the scalp spatial pattern of the intracranial dipolar current responsible of the observed EEG. In this review we begin by placing the BSS linear instantaneous model of EEG wi...

5 Blind Source Separation (BSS) plays a key role to analyze multichannel data since it aims at recovering unknown underlying elementary sources from observed linear mixtures in an unsupervised way. In a large number of applications, multichannel measurements contain corrupted entries, which are highly detrimental for most BSS techniques. In this article, we introduce a 10 new robust BSS techniq...