Results 281 to 290 of about 10,574,194 (321)

Designing multichannel source separation based on single-channel source separation

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015
In this paper, an extension of independent vector analysis (IVA), model-based IVA, is proposed for multichannel source separation. For obtaining better source models, we introduce a single-channel source separation method, and utilize the outputs as source variances in time-frequency-variant Gaussian source model. The demixing matrices are estimated in
Ono, Nobutaka, Remes, Ulpu, Palomäki, Kalle, Kurimo, Mikko, Ramirez Lopez, Ana   +5 more
openaire   +5 more sources

Second Order Nonstationary Source Separation

Journal of VLSI signal processing systems for signal, image and video technology, 2002
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Choi, SJ, Cichocki, A, Belouchrani, A
openaire   +2 more sources

Performance analysis of source separation based on blind source separation

IET International Radar Conference 2015, 2015
Source separation plays an important role in array signal processing applications, such as anti-jamming, multisignal detection, etc. The performance of source separation need to be analyzed, which can also be indicated by the array performance index, output signal-interference-noise-ratio (SINR) and beam pattern.
Yang Gao Yang Gao, Jia Xu Jia Xu, Huachao Hu Huachao Hu, Xiuhua Wang Xiuhua Wang   +3 more
openaire   +1 more source

Geometric source separation: merging convolutive source separation with geometric beamforming

IEEE Transactions on Speech and Audio Processing, 2002
Convolutive blind source separation and adaptive beamforming have a similar goal-extracting a source of interest (or multiple sources) while reducing undesired interferences. A benefit of source separation is that it overcomes the conventional cross-talk or leakage problem of adaptive beamforming.
L. Parra, C. Alvino
openaire   +1 more source

Blind source separation

2019
This paper presents a mathematical approach to methods of blind sources separation(BSS) such as principal component analysis(PCA) and independent component analysis(ICA).
openaire   +2 more sources

Audio Source Separation

2002
Abstract In 1991 Jutten [10] proposed a Neural Network for separating out independent signals from a set of mixtures. This has led to the development of Independent Component Analysis (ICA) or Blind Signal Separation (BSS). The problem is deceivingly simple. Currently a number of extensions to ICA are being explored.
openaire   +1 more source

A blind source separation technique using second-order statistics

IEEE Transactions on Signal Processing, 1997
A. Belouchrani, K. Abed-Meraim, J. Cardoso, É. Moulines   +3 more
semanticscholar   +1 more source

Time-shift denoising source separation

Journal of Neuroscience Methods, 2010
I present a new method for removing unwanted components from neurophysiological recordings such as magnetoencephalography (MEG), electroencephalography (EEG), or multichannel electrophysiological or optical recordings. A spatiotemporal filter is designed to partition recorded activity into noise and signal components, and the latter are projected back ...
openaire   +2 more sources

Removing electroencephalographic artifacts by blind source separation.

Psychophysiology, 2000
Tzyy-Ping Jung, Tzyy-Ping Jung, S. Makeig, Colin Humphries, Te-Won Lee, Te-Won Lee, M. Mckeown, V. Iragui, T. Sejnowski, T. Sejnowski   +9 more
semanticscholar   +1 more source

Audio Source Separation

2013
In order to enhance the (audio) signal of interest in the case of added audio sources, one can aim at their separation. Albeit being very demanding, Audio Source Separation of audio signals has many interesting applications: for example, in Music Information Retrieval, it allows for polyphonic transcription or recognition of lyrics in singing after ...
openaire   +1 more source