7,781 research outputs found
Non-negative mixtures
This is the author's accepted pre-print of the article, first published as M. D. Plumbley, A. Cichocki and R. Bro. Non-negative mixtures. In P. Comon and C. Jutten (Ed), Handbook of Blind Source Separation: Independent Component Analysis and Applications. Chapter 13, pp. 515-547. Academic Press, Feb 2010. ISBN 978-0-12-374726-6 DOI: 10.1016/B978-0-12-374726-6.00018-7file: Proof:p\PlumbleyCichockiBro10-non-negative.pdf:PDF owner: markp timestamp: 2011.04.26file: Proof:p\PlumbleyCichockiBro10-non-negative.pdf:PDF owner: markp timestamp: 2011.04.2
Mathematical tools for identifying the fetal response to physical exercise during pregnancy
In the applied mathematics literature there exist a significant number of tools that can reveal the interaction between mother and fetus during rest and also during and after exercise. These tools are based on techniques from a number of areas such as signal processing, time series analysis, neural networks, heart rate variability as well as dynamical systems and chaos. We will briefly review here some of these methods, concentrating on a method of extracting the fetal heart rate from the mixed maternal-fetal heart rate signal, that is based on phase space reconstructio
Blind separation of speech signals based on lattice-ica geometric procedure
International audienc
Simulated Annealing, High-Order Statistics and Mutual Information for Separation of Sources
In this article, the fusion of a stochastic metaheuristic as
Simulated Annealing (SA) with classical criteria for convergence
of Blind Separation of Sources (BSS), is shown. Although the
topic of BSS, by means of various techniques, including ICA,
PCA, and neural networks, has been amply discussed in the
literature, to date the possibility of using simulated annealing
algorithms has not been seriously explored. From experimental
results, this paper demonstrates the possible benefits offered by
SA in combination with high order statistical and mutual
information criteria for BSS, such as robustness against local
minima and a high degree of flexibility in the energy function
Convolutive Blind Source Separation Methods
In this chapter, we provide an overview of existing algorithms for blind source separation of convolutive audio mixtures. We provide a taxonomy, wherein many of the existing algorithms can be organized, and we present published results from those algorithms that have been applied to real-world audio separation tasks
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