Title:
METHOD OF AND SYSTEM FOR BLIND EXTRACTION OF MORE THAN TWO PURE COMPONENTS OUT OF SPECTROSCOPIC OR SPECTROMETRIC MEASUREMENTS OF ONLY TWO MIXTURES BY MEANS OF SPARSE COMPONENT ANALYSIS
Document Type and Number:
WIPO Patent Application WO/2010/058230
Kind Code:
A3
Abstract:
The present invention generally relates to a computer-implemented system for processing data for the purpose of blind extraction of more than two pure components from two mixtures recorded in the fields of spectroscopy and spectrometry. Specifically, the invention is related to the application of the method of sparse component analysis, also known as underdetermined blind source separation, to blind decomposition of spectroscopic data consisting of two mixtures X into more than two pure components S and concentration matrix A. Spectroscopic data refers to data gathered by nuclear magnetic resonance (NMR) spectroscopy, electron paramagnetic resonance (EPR) spectroscopy, infrared (IR) spectroscopy, ultraviolet (UV) spectroscopy, Raman spectroscopy or mass spectrometry. Two mixtures are either analyzed in a recording domain or in a first new representation domain by using linear transform T1, wherein pure components in the first new representation domain are sparser than in the recording domain. The number of pure components and mixing matrix are estimated in either the recording domain or the first new representation domain by means of a data clustering algorithm. The pure components are estimated by means of linear programming, convex programming with quadratic constraint (l2-norm based constraint) or quadratic programming method with I1-norm based constraint in either the recording domain, the first new representation domain or the second new representation domain, wherein the second new representation domain is obtained through another linear transform T2 and the second new representation domain must be the domain where the results are presented. The estimated pure components are ranked using negentropy based criterion. Components with negentropy measure that differs 10 orders of magnitudes or more from the negentropy of the majority of the components are classified as outliers and eliminated. If pure components are estimated in the first new representation domain, inverse transform T1
-1 is applied to estimate pure components to transfrom them back into recording domain of the two mixtures.
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Inventors:
IVICA KOPRIVA (HR)
IVANKA JERIC (HR)
VILKO SMRECKI (HR)
IVANKA JERIC (HR)
VILKO SMRECKI (HR)
Application Number:
PCT/HR2008/000037
Publication Date:
December 08, 2011
Filing Date:
November 24, 2008
Export Citation:
Assignee:
INST RUDJER BOSKOVIC (HR)
IVICA KOPRIVA (HR)
IVANKA JERIC (HR)
VILKO SMRECKI (HR)
IVICA KOPRIVA (HR)
IVANKA JERIC (HR)
VILKO SMRECKI (HR)
International Classes:
G06K9/62; G01R33/46
Other References:
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MOVAHEDI NAINI F ET AL: "Estimating the mixing matrix in Sparse Component Analysis (SCA) based on partial k-dimensional subspace clustering", NEUROCOMPUTING, ELSEVIER SCIENCE PUBLISHERS, AMSTERDAM, NL, vol. 71, no. 10-12, 1 June 2008 (2008-06-01), pages 2330 - 2343, XP022703822, ISSN: 0925-2312, [retrieved on 20080215], DOI: 10.1016/J.NEUCOM.2007.07.035
ZIBULEVSKY M ET AL: "Blind source separation by sparse decomposition in a signal dictionary", 1 January 2001, INDEPENDENT COMPONENT ANALYSIS: PRINCIPLES AND PRACTICE, CAMBRIDGE UNIVERSITY PRESS, PAGE(S) 181 - 208, ISBN: 978-0-521-79298-1, XP008143700
PANDO GEOL'GIEV ET AL: "Sparse Component Analysis: A New Tool for Data Mining", 1 January 2007 (2007-01-01), XP008143662, ISSN: 1931-6828, ISBN: 0-387-69318-1, Retrieved from the Internet
WEI ZHANG ET AL: "A New Two-Stage Approach to Underdetermined Blind Source Separation using Sparse Representation", 2007 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING 15-20 APRIL 2007 HONOLULU, HI, USA, IEEE, PISCATAWAY, NJ, USA, 15 April 2007 (2007-04-15), pages III - 953, XP031463629, ISBN: 978-1-4244-0727-9
KUDO M ET AL: "Performance Analysis of Minimum>tex<$ell_1$>/tex<-Norm Solutions for Underdetermined Source Separation", IEEE TRANSACTIONS ON SIGNAL PROCESSING, IEEE SERVICE CENTER, NEW YORK, NY, US, vol. 52, no. 3, 1 March 2004 (2004-03-01), pages 582 - 591, XP011107793, ISSN: 1053-587X, DOI: 10.1109/TSP.2003.822284
SHOJI MAKINO ET AL: "Blind Speech Separation", 1 January 2007, SPRINGER, pages: 271 - 304, XP002660485
FOO-TIM CHAU ET AL: "Chapter 11 Applications of wavelet transform in spectroscopic studies 0110 0229", 1 January 2000, WAVELETS IN CHEMISTRY, ELSEVIER SCIENCE PUBLISHERS B.V, NL, PAGE(S) 241 - 262, ISBN: 978-0-444-50111-0, XP008143461
SATU-PIA REINIKAINEN ED - ALEXEY L POMERANTSEV (ED): "Wavelets in compressing spectral data", 1 January 2005, PROGESS IN CHEMOMETRICS RESEARCH : [COLLECTED PAPERS OF SCIENTISTS, WHO PARTICIPATED IN THE THIRD WINTER SCHOOL ON CHEMOMETRICS (WSC-3) HELD IN RUSSIA, IN PUSHKINSKIE GORY VILLAGE (NEAR PSKOV CITY), 2004], NOVA SCIENCE PUBL, NEW YORK, NY, USA, PAGE(S, ISBN: 978-1-59454-257-2, XP008143546
TIMOTHY D W CLARIDGE ED - TIMOTHY D W CLARIDGE: "Chapter 2 Introducing high-resolution NMR", 1 January 2000, HIGH-RESOLUTION NMR TECHNIQUES IN ORGANIC CHEMISTRY, PERGAMON, NETHERLANDS, PAGE(S) 13 - 44, ISBN: 0-08-042799-5, XP008143545
ATTA-UR-RAHMAN ET AL: "Passage of Chapter 1 - The Basics of Modern NMR Spectroscopy", 1 January 1996, SOLVING PROBLEMS WITH NMR SPECTROSCOPY, ACADEMIC PRESS, US, PAGE(S) 20 - 89, ISBN: 0-12-066320-1, XP008143540
LESLIE D. FIELD: "Organic Structures from Spectra", 1 January 2008, WILEY, pages: 32 - 61, XP008143729
TERRY M PETERS ET AL: "Chapter 4 - The Fourier Transform in Magnetic Resonance Imaging", 1 January 1998, THE FOURIER TRANSFORM IN BIOMEDICAL ENGINEERING (APPLIED AND NUMERICAL HARMONIC ANALYSIS), BIRKHÄUSER, BOSTON, MASS., USA, PAGE(S) 89 - 128, ISBN: 0-8176-3941-1, XP008143538
Attorney, Agent or Firm:
VUKMIR & ASSOCIATES (Zagreb, HR)
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