Linear Prediction (LN) (requires 1D or full version)
This command performs either forward or backward linear prediction, depending on parameters set by the user. Backward prediction can be used to correct corrupted early data points, which cause rolling baselines. Forward prediction is used to predict data out to twice the actual acquisition time, and is used with severely truncated data, such as in the indirect dimension of 2D experiments as an alternative to zero-filling.
When the LN command is issued, a dialog box is displayed prompting for the following values:
For backward prediction (which is the default), the user must set the number of points to back predict, the number of data points upon which to base the prediction and the number of frequencies to predict. The default value for number of points to back predict is 2 and should usually be a small number (4 or less). Larger values may cause failure of the prediction algorithm. The number of data points on which the prediction is based must be less than half the total number of data points, or the algorithm fails. The larger this value, the longer the prediction process will take. The default value is 64. The number of frequencies to predict is usually unknown, but usually a small value can be used. The larger the value, the higher the chances that the algorithm will fail. The default value is 8.
For forward prediction, the user must select the Forward Prediction button in the dialog box. Forward linear prediction always doubles the number of data points. The value for number of points to back predict is ignored.
LN parameters can also be set from the command line (and so can be used in macros). Allowed commands are shown below. Once parameters are set, the LN command with no arguments initiates the linear prediction using the current settings.
LN forward
LN back
LN points n - set the number of points to predict to n. This applies to backward prediction only, as forward prediction always doubles the data size.
LN signals n - set the maximum number of signals for the prediction to n
LN dimensions n (or LN dim n) - set the number of points on which to base the prediction to n. The larger the number, the more time the calculation will take.
Last updated: 8/2/06