US 2021/0201140 A1Published application

Sample analysis apparatus and sample analysis program

AssigneeFemto Deployments Inc.

InventorsAkira WATANABE, Tadashi OKUNO, Takeji UEDA

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Abstract

A learning model creation unit 12A that creates a learning model using parameters of a plurality of fitting functions corresponding to a generation source of a composite waveform fit to a frequency spectrum obtained by spectroscopic measurement of a terahertz wave, and a sample information prediction unit 22A that applies a parameter obtained for a sample to be predicted to the learning mode thereby predicting information about the sample to be predicted are included, and the information about the sample to be predicted can be more accurately predicted using a learning model in which a feature quantity representing a property of a sample is reflected as the parameters of the plurality of fitting functions corresponding to the generation source of the composite waveform fit to the frequency spectrum.

Claims21

Dependent claims

A sample analysis apparatus comprising:

a learning model storage unit that stores a learning model for predicting information about a sample using a parameter determining a property for each of a plurality of fitting functions corresponding to a generation source of a composite waveform fit to a frequency spectrum obtained by spectroscopic measurement of the sample using a terahertz wave;
a learning parameter calculation unit as a parameter calculation unit that acquires, for each of a plurality of learning samples, each frequency spectrum obtained by spectroscopic measurement of the sample using the terahertz wave, and analyzes the acquired frequency spectrum to calculate each parameter;
and
a learning model creation unit that creates the learning model using the parameter calculated for each of the plurality of learning samples by the learning parameter calculation unit and information about the plurality of learning samples as learning data, and causes the learning model storage unit to store the created learning model,
wherein the parameter calculation unit includes
a thinning processing unit that thins out a property value at a frequency at which absorption of the terahertz wave by water vapor other than the sample becomes large among property values for respective frequencies in the frequency spectrum,
a fitting processing unit that fits a composite waveform of the plurality of fitting functions to the property value thinned by the thinning processing unit, and
a parameter acquisition unit that acquires, as the parameter, a value determining a property of each of the plurality of fitting functions used for fitting.

5 more elements

A sample analysis program implemented on a sample analysis apparatus that stores, in a learning model storage unit, a learning model for predicting information about a sample using a parameter determining a property for each of a plurality of fitting functions corresponding to a generation source of a composite waveform fit to a frequency spectrum obtained by spectroscopic measurement of the sample using a terahertz wave, the sample analysis program causing a computer of the sample analysis apparatus to function as:

learning parameter calculation means as parameter calculation means that acquires, for each of a plurality of learning samples, each frequency spectrum obtained by spectroscopic measurement of the sample using the terahertz wave, and analyzes the acquired frequency spectrum to calculate each parameter;
and
learning model creation means that creates the learning model using the parameter calculated for each of the plurality of learning samples by the learning parameter calculation means and information about the plurality of learning samples as learning data, and causes the learning model storage unit to store the created learning model,
wherein the parameter calculation means includes
thinning processing means that thins out a property value at a frequency at which absorption of the terahertz wave by water vapor other than the sample becomes large among property values for respective frequencies in the frequency spectrum,
fitting processing means that fits a composite waveform of the plurality of fitting functions to the property value thinned by the thinning processing means, and
parameter acquisition means that acquires, as the parameter, a value determining a property of each of the plurality of fitting functions used for fitting.

4 more elements

Dependencies are inferred from the claim text.