Hi,
I have measured data for transmission lines with varying sizes and lengths. I also have a physics-based model for the lines. I need to fit the parameters of the model to the measured data, where the parameters are scalable with the device dimensions. In other words, the parameters depend on the dimensions of the transmission lines. The end result is just one model with dimensions of the transmission lines as its parameters.
Is there any way to do this using ADS (e.g. Optimization) ?
Thanks,
Vipul
I have measured data for transmission lines with varying sizes and lengths. I also have a physics-based model for the lines. I need to fit the parameters of the model to the measured data, where the parameters are scalable with the device dimensions. In other words, the parameters depend on the dimensions of the transmission lines. The end result is just one model with dimensions of the transmission lines as its parameters.
Is there any way to do this using ADS (e.g. Optimization) ?
Thanks,
Vipul
I believe the answer is yes you can use optimization for this. However how you organize the data is important so that it can be accessed during simulation. Also your physics based model needs to be capable of fitting the data in all the dimensions you want.
Why do all this when you can create a multidimensional data file (multidimensional MDIF) and use it instead of your model. I like this approach because there will be no loss of accuracy and a lot of less work. Unless I am missing something else you are trying to accomplish.