onvolutive blind source separation (BSS) usually encounters two difficulties – the filter indeterminacy in the recovered sources and the relatively high computational load. In this paper we propose an efficient method to convolutive BSS, by dealing with these two issues. It consists of two stages, namely, multichannel blind deconvolution (MBD) and learning the postfilters with the minimum filte...

FeedForward (FF-) Blind Source Separation (BSS) systems have some degree of freedom in the solution space. Therefore, signal distortion is likely to occur. First, a criterion for the signal distortion is discussed. Properties of conventional methods proposed to suppress the signal distortion are analyzed. Next, a general condition for complete separation and distortion-free is derived for multi...

Blind Source Separation (BSS) algorithms have often been interpreted as a set of blind adaptive beamformers. Although this interpretation does not entirely hold under realistic conditions, it gives some useful insights on the self-steering capacity of BSS techniques. Actually, while accurate source location information is usually necessary to steer a beamformer, BSS offers the possibility to re...

This paper addresses the tracking capability of blind source separation algorithms for rapidly time-varying sensor or source positions. Based on a known algorithm for blind source separation, which also allows for simultaneous localization of multiple active sources in reverberant environments, the source separation performance will be investigated for abrupt microphone array rotations represen...

Blind source separation (BSS) addresses the problem of separating multi­ channel signals observed by generally spatially separated sensors into their constituent underlying sources. The passage of these sources through an un­ known mixing medium results in these observed multichannel signals. This study focuses on BSS, with special emphasis on its application to the tem­ poromandibular joint di...

In the practical environment, it is difficult for the user receiver to get DOA information of GPS signals in advance. In this paper, on the basis of blind source separation (BSS) theory, a signal-separation-based GPS antiinterference algorithm is proposed. In accordance with BSS process modes, wavelet denoising algorithm is first adopted to restrain the influence of noise on separation algorith...

The performances of blind source separation (BSS) are still not satisfiable to apply to the real environments. The major obstacle may seem the finite filter length of the assumed mixing model and the nonlinear sensor noises. This paper presents a two-step speech enhancement method with stereo microphone inputs. The first is an ordinary frequency-domain BSS step, and the second is the removal of...

Signal processing methods for speech enhancement are of vital interest for communications equipments. In particular, multichannel algorithms, which perform spatial filtering to separate signals that have overlapping frequency content but different spatial origins, are important for a wide range of applications. Two of the most popular multichannel methods are blind signal separation (BSS) and b...

Frequency domain Blind Source Separation (BSS) is shown to be equivalent to two sets of Adaptive Beamformers (ABFs). The minimization of the off-diagonal components in the BSS update equation can be viewed as the minimization of the mean square error in the ABF. The unmixing matrix of the BSS and the filter coefficients of the ABF converge to the same solution in the mean square error sense if ...