SModel is used to compute the weighted difference between two sets of S-parameters. The weighted difference (error function) calculation method is selected by setting the "Error Function" measurement parameter. This measurement can be used as a goal for optimization when fitting a circuit to measured S-parameter data.

SModel requires that the two sets of S-parameters have the same number of frequencies, and compares them in order, point by point. It does not require that the frequency values be identical. For example, you can use SModel to compare a physically scaled model against the original, even though their operation frequencies are different. You should make sure the frequencies are set correctly on the source of each set of S-parameters.

Name | Type | Range |
---|---|---|

Data Source Name | Subcircuit | 1 to 1000 ports |

Data Source Name | Subcircuit | 1 to 1000 ports |

Error Function | List of options |
Average L1 Norm Average L2 Norm Maximum L1 Norm Average Normalized L1 Norm |

**NOTE:** All measurements will have additional parameters that
allow you to specify the plotting configuration for swept parameters. These parameters are
dynamic; they change based upon which data source is selected. See “Swept Parameter Analysis ” for details on configuring these parameters.

This measurement returns a real value. Select the dB check box to display the absolute value of the real component in dB.

The various error functions are calculated as follows:

**Average L1 Norm.** The weighted difference is the average
magnitude of the difference between each element of the S-parameter matrix:

**Average L2 Norm.** The weighted difference is the average
squared magnitude of the difference between each element of the S-parameter matrix:

**Maximum L1 Norm.** The maximum difference is the magnitude of
the maximum difference between each element of the S-parameter matrix (the magnitude of the
largest difference between any pair of entries in the S-parameter matrices):

**Average Normalized L1 Norm.** The magnitude of the difference
between each element of the S-parameter matrix is calculated. Each difference is then normalized
by the average magnitude of the two matrix elements (one from each set):

In the previous equations, S_{A} and S_{B} are the
two NxN S-parameter matrices.

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