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Valentin G Stanev, 461758 Sharwood Pl, Crofton, MD 21114

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1758 Sharwood Pl, Crofton, MD 21114   

Darien, IL   

Naperville, IL   

Baltimore, MD   

210 Charles St, Waltham, MA 02453    781-6473846   

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Us Patents

Source Identification By Non-Negative Matrix Factorization Combined With Semi-Supervised Clustering

US Patent:
2018006, Mar 1, 2018
Filed:
Aug 29, 2017
Appl. No.:
15/690176
Inventors:
- Los Alamos NM, US
Ludmil B. Alexandrov - Santa Fe NM, US
Filip L. Iliev - Oakland CA, US
Valentin G. Stanev - Crofton MD, US
Velimir V. Vesselinov - Santa Fe NM, US
Assignee:
Los Alamos National Security, LLC - Los Alamos NM
International Classification:
G06N 99/00
Abstract:
Machine-learning methods and apparatus are provided to solve blind source separation problems with an unknown number of sources and having a signal propagation model with features such as wave-like propagation, medium-dependent velocity, attenuation, diffusion, and/or advection, between sources and sensors. In exemplary embodiments, multiple trials of non-negative matrix factorization are performed for a fixed number of sources, with selection criteria applied to determine successful trials. A semi-supervised clustering procedure is applied to trial results, and the clustering results are evaluated for robustness using measures for reconstruction quality and cluster separation. The number of sources is determined by comparing these measures for different trial numbers of sources. Source locations and parameters of the signal propagation model can also be determined. Disclosed methods are applicable to a wide range of spatial problems including chemical dispersal, pressure transients, and electromagnetic signals, and also to non-spatial problems such as cancer mutation.

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