Neural network system and methods for analysis of organic materials and structures using spectral data
Apparatus and processes are described for recognizing and identifying materials. Characteristic spectra are obtained for the materials via spectroscopy techniques including nuclear magnetic resonance spectroscopy, infrared absorption analysis, x-ray analysis, mass spectroscopy and gas chromatography. Desired portions of the spectra may be selected and then placed in proper form and format for presentation to a number of input layer neurons in an offline neural network. The network is first trained according to a predetermined training process; it may then be employed to identify particular materials. Such apparatus and processes are particularly useful for recognizing and identifying organic compounds such as complex carbohydrates, whose spectra conventionally require a high level of training and many hours of hard work to identify, and are frequently indistinguishable from one another by human interpretation.
- DOE Contract Number:
- FG09-85ER13426; FG09-87ER13810
- Assignee:
- Univ. of Georgia Research Foundation, Inc., Athens, GA (United States)
- Patent Number(s):
- A; US 5218529
- Application Number:
- PPN: US 7-559649
- OSTI ID:
- 6047833
- Country of Publication:
- United States
- Language:
- English
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Related Subjects
400100* -- Analytical & Separations Chemistry
99 GENERAL AND MISCELLANEOUS
990200 -- Mathematics & Computers
ABSORPTION SPECTROSCOPY
CARBOHYDRATES
CHROMATOGRAPHY
DATA ANALYSIS
DESIGN
EDUCATION
ELECTROMAGNETIC RADIATION
GAS CHROMATOGRAPHY
INFRARED RADIATION
MAGNETIC RESONANCE
MASS SPECTROSCOPY
NEURAL NETWORKS
NUCLEAR MAGNETIC RESONANCE
OPERATION
ORGANIC COMPOUNDS
RADIATIONS
RESONANCE
SEPARATION PROCESSES
SPECTRA
SPECTROSCOPY
TRAINING
X-RAY SPECTROSCOPY