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This paper proposes online independent vector analysis (IVA) based on an auxiliary-function approach for real-time blind speech separation. A batch auxiliary-function approach is naturally extended with autoregressive approximation of an auxiliary variable. Experimental evaluations show that the proposed online algorithm works in real time and attains relatively high signal-to-interference ratios...
Extraction of unknown independent source signals from a noisy mixture is a fundamental problem in most signal processing applications. The existing independent component analysis (ICA) algorithms have tackled this problem for complex and real valued mixtures for both super and sub Gaussian sources. However in reality super and sub Gaussian sources exist collectively in a mix. It was observed when...
Nonnegative Matrix Factorization (NMF) is a powerful tool for decomposing mixtures of non-stationary signals in the Time-Frequency (TF) domain. However, unlike the High Resolution (HR) methods dedicated to mixtures of exponentials, its spectral resolution is limited by that of the underlying TF representation. In this paper, we propose a unified probabilistic model called HR-NMF, that permits to overcome...
This paper presents stable and fast update rules for independent vector analysis (IVA) based on auxiliary function technique. The algorithm consists of two alternative updates: 1) weighted covariance matrix updates and 2) demixing matrix updates, which include no tuning parameters such as step size. The monotonic decrease of the objective function at each update is guaranteed. The experimental evaluation...
We present a model-based approach to separating and transcribing single-channel, multi-instrument polyphonic music in a semi-blind fashion. Our system extends the non-negative matrix factorization (NMF) algorithm to incorporate constraints on the basis vectors of the solution. In the context of music transcription, this allows us to encode prior knowledge about the space of possible instrument models...
This paper prepares a review of ICA based approaches that are used for separation of components in functional MRI sequences. In previous works, the FastICA and the Infomax algorithms are investigated in more details; therefore, in this paper we focus on methods such as "radical ICA", "SDD ICA", "Erica" and "Evd" for separation purposes. This comparative study...
A method is presented to non-invasively separate the fetal phonocardiograms (FPCG) of the fetuses in a multiple fetus pregnancy. The method uses a device like a stethoscope. We assume that the phonocardiograms of the fetuses are statistically independent. Results of simulations are included in the paper.
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