Work

State identification in data with a temporal dimension

Year: 2016

Type: article

Abstract: States are identified in a time ordered sequence of data that have a temporal component. Data that includes a plurality of snapshots is received. Each snapshot of the plurality of snapshots includes a plurality of sensor measurements captured from distinct sensors at a common time point. The plurality of snapshots are time ordered. Root mean square error (RMSE) values are computed between successive pairs of the plurality of snapshots in time order. A peak is identified in the computed RMSE values. A valley is identified in the computed RMSE values. A stable state is determined as occurring from the identified peak to the identified valley. The determined stable state is output.

Source: University of Chicago

DOI: 10.6082/bn492-b9s93

Authors: Cacioppo, Stephanie, Cacioppo, John T., Weiss, Robin M.

Institution: University of Chicago

Language: English

Topic: Fault Detection and Control Systems

Subfield: Control and Systems Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: green

OpenAlex ID: W7163067857

FWCI:

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