Use the sample multiplier field to configure the Time to Steady State (TSS), the estimated time (in seconds) for the process to completely respond to changes in inputs. The Time to Steady State (TSS) is calculated as:
TSS = 50 × Data Sampling Rate × Sample Multiplier.
The Data Sampling Rate (DSR) is the Historian Sampling rate entered in the NN function block Properties dialog. If you are using data from a file, the sampling rate in the file is read as the Data Sampling Rate for the TSS calculation.
The Sample Multiplier is the factor at which data from the given data set (created by sampling at the Data Sampling Rate) is sampled for creating the neural net model. For example, Sample Multiplier of one (1) means all the samples at the DSR are used, while Sample Multiplier of two (2) implies that only every second sample from the data set is going to be used for training, half of the former case. In effect, the product of DSR and Sample Multiplier establishes the effective sampling rate of the data to be used for training.
To modify the TSS, edit the Sample Multiplier according to the formula above. For example, if Historian Sampling Rate is one second and the process TSS is estimated to be 100 seconds, set the Sample Multiplier to two (2). If you are using data from a file in which the sampling rate is two seconds, the minimum possible TSS is 100 seconds (Sample Multiplier = 1). Other possible TSS values are 200 seconds, 300 seconds, and so on for Sample Multipliers of 2, 3, and so on.
When using the NN block in conjunction with an LE block for lab analysis samples, note that the TSS value establishes the maximum sample delay that affects the NN block's automatic correction mechanism.