Machine learning and rate-distortion cost functions for enabling the optimization of device calibration

A method, non-transitory computer readable medium, and apparatus for applying a cost function to calculate an optimal value of a single variable for a calibration application are disclosed. For example, the method identifies the single variable of the calibration application, applies a cost function...

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Bibliographische Detailangaben
1. Verfasser:	Schweid Stuart A
Format:	Patent
Sprache:	eng
Schlagworte:	ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVEREDIN A SINGLE OTHER SUBCLASS CALCULATING COLORIMETRY COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING MEASUREMENT OF INTENSITY, VELOCITY, SPECTRAL CONTENT,POLARISATION, PHASE OR PULSE CHARACTERISTICS OF INFRA-RED,VISIBLE OR ULTRA-VIOLET LIGHT MEASURING MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR PHYSICS RADIATION PYROMETRY TARIFF METERING APPARATUS TESTING
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Beschreibung
Zusammenfassung:	A method, non-transitory computer readable medium, and apparatus for applying a cost function to calculate an optimal value of a single variable for a calibration application are disclosed. For example, the method identifies the single variable of the calibration application, applies a cost function to the single variable, wherein the cost function comprises a function of a fit error plus a regularization weighting parameter (λ) times a regularization cost, calculates the optimal value of the single variable based upon the cost function that is applied to the single variable and uses the optimal value of the single variable to generate a calibration matrix used for the calibration application.