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Semiconductor Modeling:

For Simulating Signal, Power, and Electromagnetic Integrity
Sofort lieferbar | Lieferzeit: Sofort lieferbar I
Roy Leventhal
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Discusses process variation, model accuracy, design flow and many other practical engineering, reliability and manufacturing issues
"Semiconductor Modeling: For Simulating Signal, Power, and Electromagnetic Integrity assists engineers - both recent graduates and working product designers - in designing high-speed circuits. The authors apply circuit theory, circuit simulation tools, and practical experience to help the engineer understand semiconductor modeling as applied to high-speed digital designs. The emphasis is on semiconductor modeling, with PCB transmission line effects, equipment enclosure effects, and other modeling issues discussed as needed. The text addresses many practical considerations, including process variation, model accuracy, validation and verification, signal integrity, and design flow. Readers will benefit from its survey of modeling for semiconductors, packages, and interconnects, along with usable advice on how to get complex, high-speed prototypes to work on the first try.
How the Workplace Supports Successful Design.- to Modeling Concepts.- Generating Models.- Model Properties Derived from Device Physics Theory.- Measuring Model Properties in the Laboratory.- Using Statistical Data to Characterize Component Populations.- Selecting Components and Their Models.- Using Selection Guides to Compare and Contrast Components.- Using Data Sheets to Compare and Contrast Components.- Selecting the Best Model for a Simulation.- Modeling and Simulation in the Design Process Flow.- About the IBIS Model.- Key Concepts of the IBIS Specification.- Using IBIS Models in What-If Simulations.- Fixing Errors and Omissions in IBIS Models.- Using EDA Tools to Create and Validate IBIS Models from Spice.- Managing Models.- Sources of IBIS Models.- Working with the Model Library.- Model Accuracy and Verification.- Methodology for Verifying Models.- Verifying Model Accuracy by Using Laboratory Measurements.- Balancing Accuracy Against Practicality When Correlating Simulation Results.- Deriving an Equation-Based Model from a Macromodel.- Future Directions in Modeling.- The Challenge to Ibis.- Feedback to the Model Provider Improves Model Accuracy.- Future Trends in Modeling.- Using Probability: The Ultimate Future of Simulation.

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