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[SOLVED] ADS - Finding Derivatives

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Newbie level 3
Nov 29, 2012
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I have a circuit model in Agilent ADS with several parameters to optimize (a couple of inductors and capacitators).
after optimization i would like to find out the derivatives (Numerical) of the S-Params by several variables, for example d(S11)/d(l1) - (l1 is an inductor in the design).
I would like to calculate those in several frequencies in the range of (1-25 GHz).

What is the better approach to do so? using a sweep or MATLAB?
And could you please specify how to do it?


If you use one single sweeping variable like inductor value,you should use "diff()" function.If there are many variable, collecting the data and process them in Matlab environment will be easier.

Thanks for your advice BigBoss, could you please elaborate on how to fetch the data to MATLAB efficiently ?


ADS can do this calculation for you directly. Once a schematic has been optimized it is possible just to reset the Optimization mode to Sensitivity and it will calculate the sensitivity for each optimizable parameter value against any defined scaler measurement, eg d(MAG(S11))/d(L1) or d(GAIN)/d(C1). The absolute sensitivity value is exactly the derivative you are wanting to compute but you can also compute the normalized value too.

See the following video tutorial for and example:

This method calculates the sensitivity versus the parameter value when only that one value is being perturbed. This is, to some extent, not realistic though in a real circuit. What would normally be happening is that all values are randomly changing at the same time. This can be modelled in ADS using Monte Carlo Analysis. Using this sort of technique it is possible to then plot yield sensitivity histograms which can also documant the component sensitivity of any defined measurement to investigate which parameter has most effect on the circuit performance.

Part d of the following set of tutorial videos covers Yield Sensitivity Histograms:
Thanks! this is exactly what i was looking for, very helpful

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