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Design for Manufacturability and Statistical Design: A Constructive Approach provides a thorough treatment of the causes of variability, methods for statistical data characterization, and techniques for modeling, analysis, and optimization of integrated circuits to improve yield. The objective of the constructive approach developed in this book is to formulate a consistent set of methods and principles necessary for rigorous statistical design and design for manufacturability from device physics to large-scale circuit optimization. The segments of the book are devoted, respectively, to
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Produktbeschreibung
Design for Manufacturability and Statistical Design: A Constructive Approach provides a thorough treatment of the causes of variability, methods for statistical data characterization, and techniques for modeling, analysis, and optimization of integrated circuits to improve yield. The objective of the constructive approach developed in this book is to formulate a consistent set of methods and principles necessary for rigorous statistical design and design for manufacturability from device physics to large-scale circuit optimization. The segments of the book are devoted, respectively, to



  • understanding the causes of variability;


  • design of test structures for variability characterization;


  • statistically rigorous data analysis;


  • techniques of design for manufacturability in lithography and in chemical mechanical polishing;


  • statistical simulation, analysis, and optimization techniques for improving parametric yield.




Design for Manufacturability and Statistical Design: A Constructive Approach presents an overview of the methods that need to be mastered for state-of-the-art design for manufacturability and statistical design methodologies. It is an important reference for practitioners and students in the field of computer-aided design of integrated circuits.


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Autorenporträt
Michael Orshansky, University of Texas at Austin, Austin, TX, USA / Sani Nassif, IBM, Austin, TX, USA / Duane Boning, MIT, Cambridge, MA, USA