  We propose that the Matrix Profile data structure, conventionally applied to
large scale time-series data mining, is applicable to the analysis and
suppression of cyclical error in electromechanical systems, paving the way for
an intelligent family of adaptable control systems which respond to
environmental error at a computational cost low enough to be practical in
embedded applications. We construct and evaluate the efficacy of a control
algorithm utilizing the Matrix Profile, which we call Cyclical
Electromechanical Error Denial System (CEEDS).
