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AssigneeThe Research Foundation for The State University of New York
InventorsAnatoly Frenkel, Janis Timosenko
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A method of supervised machine learning-based spectrum analysis information, using a neural network trained with spectrum information, to identify a specified feature of a given material, a system for supervised machine learning-based spectrum analysis, and a method of training a neural network to analyze spectrum data. The method of supervised machine learning-base spectrum analysis comprises inputting into the neural network spectrum data obtained from a sample of the given material; and the neural network processing the spectrum data, in accordance with the training of the neural network, and outputting one or more values for the specified feature of the sample of the material. In an embodiment, the training set of data includes x-ray absorption spectroscopy data for the given material. In an embodiment, the training set of data includes electron energy loss spectra (EELS) data.
A method of supervised machine learning-based spectrum analysis, using a neural network trained with spectrum information to identify a specified feature of a given material, the method comprising:
A system for supervised machine learning-based spectrum analysis, the system comprising:
A method of training a neural network to analyze spectrum data, the method comprising:
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