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...

The redox mechanism of two trisubstituted triazole-linked phenyl derivatives (CL41 and CL42) and a disubstituted triazole-linked phenyl derivative (CL2r50) were studied using cyclic, differential pulse and square wave voltammetry at a glassy carbon electrode. The CL41, CL42 and CL2r50 oxidation is a complex, pH-dependent irreversible process involving the formation of electroactive products tha...

Voltammetric detection of the toxic Zn ion was investigated using a fluorine-doped graphite pencil electrode (FPE). It is notable from the study that pencils were used as reference and working electrodes. In all the experiments, a clean seawater electrolyte solution was used to yield good results. The analytical working range was attained to 10 μgL(-1). The optimized voltammetric condition was ...

In independent component analysis (ICA) an instantaneous mix of sources can be recovered using maximum Likelihood (ML). In Convolutive blind source separation (BSS) the mixture arises as a combination of di erently convolved source signals due to time delays and a reverberating acoustic environment. Instead of modeling a particular time instant now a time window of the mixed signals has to be m...

We propose a convolutive non-negative matrix factorization method to improve the intelligibility of speech signal in the context of adverse noise environment. The noise bases are prior learned with Non-negative Matrix Factorization (NMF) algorithm. A modified convolutive NMF with sparse constraint is then derived to extract speech bases from noisy speech. The divergence function is selected as ...

In this paper we present an iterative inversion (II) approach to blind source separation (BSS). It consists of a quasi-Newton method for the resolution of an estimating equation obtained from the implicit inversion of a robust estimate of the mixing system. The resulting learning rule includes several existing algorithms for BSS as particular cases giving them a novel and unified interpretation...

In this paper, we propose a new method for evaluating the separation and dereverberation performance of a convolutive blind source separation (BSS) system, and investigate a separating system obtained by employing frequency domain BSS based on independent component analysis (ICA). As a result, we reveal the acoustical characteristics of the frequency domain BSS for convolutive mixture of speech...

The blind speech separation of convolutive mixtures can be performed in the time-frequency domain. The separation problem becomes to a set of instantaneous mixing problems, one for each frequency bin, that can be solved independently by any appropiated instantaneous ICA algorithm. However, the arbitrary order of the estimated sources in each frequency, known as permutation problem, has to be so...