1. Common to both system identification and RNN techniques is the requirement for experimental data. Further, this data must be of known accuracy. The internal mathematical consistency within each data set must be guaranteed, and the consistency of the data across multiple experiments must be maintained. For system identification, and by inference RNN techniques, it has been known for decades that the accuracy and consistency of the experimental data is critical to determining an equation system which describes the physical system. As such, first and foremost, for these techniques to succeed the data must be accurate, mathematically internallyconsistent,andconsistent acrossmultipleexperimentscollectedovermultipledays. 2.1.1Data Processing, Algorithms, andData Checks
2. RCM DataProcessing:Mathematical Internal Consistency WithinEach DataSet:
3. RCM Data Processing Steps To Guarantee Consistency Across Multiple Data Sets And MultipleDays Of Testing: