Determining A Class Type Of A Sample By Clustering Locally Optimal Model Parameters
Inventors: Amos Ron, Shengnan Wang
A method for characterizing a sample includes acquiring a trace signal for the sample. A set of configurations is generated for defining modeling signals to model the trace signal. Each modeling signal is defined by a plurality of model parameters, and each configuration represents an associated modeling signal having a locally optimal score for fitting the trace signal. A classification cluster is defined in a parameter domain defined by the plurality of model parameters. The classification cluster has an associated class type. The sample is determined to have the class type associated with the classification cluster responsive to determining that at least one of the configurations in the set has a distance from the classification cluster less than a threshold.
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