Results 21 to 30 of about 10,574,194 (321)
Frontiers in Physiology, 2022 Blind source separation (BSS) methods have received a great deal of attention in electroencephalogram (EEG) artifact elimination as they are routine and standard signal processing tools to remove artifacts and reserve desired neural information.
Morteza Zangeneh Soroush +18 more
doaj +1 more source
A Separation Method for Electromagnetic Radiation Sources of the Same Frequency [PDF]
Journal of Electromagnetic Engineering and Science, 2023 To separate electromagnetic interference sources with an unknown source number, a new separation method is proposed, which includes five key steps: spatial spectrum estimation, source number and direction-of-arrival estimation, mixed matrix estimation ...
Yingchun Xiao, Yang Yang, Feng Zhu
doaj +1 more source
χ-separation: Magnetic susceptibility source separation toward iron and myelin mapping in the brain
NeuroImage, 2021 Obtaining a histological fingerprint from the in-vivo brain has been a long-standing target of magnetic resonance imaging (MRI). In particular, non-invasive imaging of iron and myelin, which are involved in normal brain functions and are ...
Hyeong-Geol Shin +12 more
semanticscholar +1 more source
Asteroid: the PyTorch-based audio source separation toolkit for researchers [PDF]
Interspeech, 2020 This paper describes Asteroid, the PyTorch-based audio source separation toolkit for researchers. Inspired by the most successful neural source separation systems, it provides all neural building blocks required to build such a system.
Manuel Pariente +13 more
semanticscholar +1 more source
Nonlinear blind source separation for sparse sources [PDF]
2016 24th European Signal Processing Conference (EUSIPCO), 2016 Blind Source Separation (BSS) is the problem of separating signals which are mixed through an unknown function from a number of observations, without any information about the mixing model. Although it has been mathematically proven that the separation can be done when the mixture is linear, there is not any proof for the separability of nonlinearly ...
Ehsandoust, Bahram +3 more
openaire +2 more sources
Sudo RM -RF: Efficient Networks for Universal Audio Source Separation [PDF]
International Workshop on Machine Learning for Signal Processing, 2020 In this paper, we present an efficient neural network for end-to-end general purpose audio source separation. Specifically, the backbone structure of this convolutional network is the SUccessive DOwnsampling and Resampling of Multi-Resolution Features ...
Efthymios Tzinis +2 more
semanticscholar +1 more source
, 2014 Blind Source Separation intends to report the new results of the efforts on the study of Blind Source Separation (BSS). This edited book collects novel research ideas and some training in BSS, independent component analysis (ICA), artificial intelligence and signal processing applications.
Xianchuan Yu, Dan Hu, Jindong Xu
+5 more sources
Membranes, 2018 Enhancement of membrane permeability at no detriment of its other performances, e.g., selectivity, is a goal-directed objective in membrane fabrication.
Mohammadamin Esmaeili +3 more
doaj +1 more source
Audio Source Separation Using Sparse Representations [PDF]
, 2010 This is the author's final version of the article, first published as A. Nesbit, M. G. Jafari, E. Vincent and M. D. Plumbley. Audio Source Separation Using Sparse Representations. In W.
Jafari, MG +3 more
core +3 more sources
Spleeter: a fast and efficient music source separation tool with pre-trained models
Journal of Open Source Software, 2020 Summary We present and release a new tool for music source separation with pre-trained models called Spleeter.
Romain Hennequin +3 more
semanticscholar +1 more source