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85199B IC-CAP Analysis Module
- Overview and Features
- Post-Purchase Upgrades
Note: Model number 85199B has been obsoleted; however, the IC-CAP Simulation and Analysys feature/capability is now included in the W8502EP/ET.
The information below is provided for reference only.
The 85199B IC-CAP Analysis Module enables analysis or simulation of device behavior using the provided ADS or SPICE3 simulators or by linking directly to supported external simulators.
Comparisons of simulated to measurement or target data can then be achieved.
The Analysis Module also includes 13 robust optimization algorithms and the Plot Optimizer. The Plot Optimizer enables quick optimizations to be set up directly from any IC-CAP plot.
The ADS Linear and Transient simulators are provided with the Analysis Module. An ADS Harmonic Balance simulator can purchased separately for use with IC-CAP.
The following simulators are included in the Analysis Module:
|Simulator||Vendor||Remote Link Supported?*|
* IC-CAP supports all simulators locally, where IC-CAP and the simulator are running on the same machine. In some cases, IC-CAP and the simulator reside on separate machines and communicate via remote link. These remote links are only supported on Solaris and LINUX operating systems
The following optimizers are provided in the Analysis Module:
|IC-CAP Optimization Algorithms|
|Levenberg-Marquardt||Non-linear search method with least-squares error function.|
|Random||Random search method with stochastic gradient error function.|
|Hybrid (Random/LM)||Combination of Random and Levenberg-Marquardt algorithms and error functions.|
|Sensitivity Analysis||Single-point or infinitesimal sensitivity analysis of a design variable. Prints partial derivatives with respect to each parameter.|
|Random (Gucker)||Random search method with least-squares error function.|
|Gradient||Gradient search method with least-squares error function.|
|Random Minimax||Random search method with minimax error function.|
|Gradient Minimax||Gradient search method with minimax error function.|
|Quasi-Newton||Quasi-Newton search method with least-squares error function.|
|Least Pth||Quasi-Newton search method with least Pth error function.|
|Minimax||Two-stage, Gauss-Newton/Quasi-Newton method with minimax error function.|
|Hybrid (Random/Quasi-Newton)||Combines the Random and Quasi-Newton search methods.|
|Genetic||Direct search method using evolving parameter sets.|
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