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OverviewThis text deals with the primary and theoretical and practical aspects of IC statistical design and covers the important issues of IC statistical design and the relevant mathematical framework. It describes a spectrum of different statistical circuit design problems, such as parametric yield optimization, generalized on-target design, variability minimization, performance tuning, and worst-case design. It also covers such topics as device statistical and worst-case modelling, design of experiments and factor screening, together with some basic tenets of fuzzy set theory and multi-objective statistical optimization. Several practical examples are used to familiarize the reader with the concepts, and demonstrate the applicability of various statistical circuit design methodologies. This book is intended as introductory reference material for various groups of IC designers, and the methodologies described provide an understanding of the complex problems of statistical circuit design, thus helping to enhance the overall quality of the ICs delivered to the customers. Full Product DetailsAuthor: Jian Cheng Zhang , M.A. StyblinskiPublisher: Springer Imprint: Springer Edition: 1995 ed. Dimensions: Width: 15.50cm , Height: 1.50cm , Length: 23.50cm Weight: 1.200kg ISBN: 9780792395515ISBN 10: 0792395514 Pages: 234 Publication Date: 28 February 1995 Audience: College/higher education , Professional and scholarly , Postgraduate, Research & Scholarly , Professional & Vocational Format: Hardback Publisher's Status: Active Availability: In Print  This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us. Table of Contents1 Introduction.- 1.1 Design for Quality and Manufacturability.- 1.2 Notation.- 1.3 Interpretation of Basic Concepts.- 1.4 Summary.- 2 Overview of IC Statistical Modeling.- 2.1 Introduction.- 2.2 Process Variations.- 2.3 Environmental Variations.- 2.4 Statistical Macromodeling.- 2.5 Summary.- 3 Design of Experiments.- 3.1 Introduction.- 3.2 Experiment Analysis.- 3.3 Orthogonal Arrays.- 3.4 Main Effect Analysis.- 3.5 Interaction Analysis.- 3.6 Taguchi Experiments.- 3.7 Summary.- 4 Parametric Yield Maximization.- 4.1 Introduction.- 4.2 Yield Estimation.- 4.3 Indirect Yield Improvement.- 4.4 Direct Yield Optimization Methods.- 4.5 Generalized and Orthogonal Array-Based Gradient Methods for Discrete Circuits.- 4.6 Gradient Methods for Integrated Circuits.- 4.7 Examples.- 4.8 Summary.- 5 Variability Minimization and Tuning.- 5.1 Introduction.- 5.2 Principles of Discrete Circuit Variability Minimization.- 5.3 Principles of IC Variability Minimization.- 5.4 Factor Screening.- 5.5 Taguchi’s on-target Design.- 5.6 Two-Stage Design Strategy.- 5.7 Example 4: CMOS Delay Circuit.- 5.8 Example 5: CMOS Clock Driver.- 5.9 Summary.- 6 Worst-Case Measure Reduction.- 6.1 Introduction.- 6.2 The ±? Transistor Modeling.- 6.3 Worst-Case Measure Minimization.- 6.4 Comments on the ±? Model.- 6.5 Creation of Worst-Case Models From the Statistical Model.- 6.6 Summary.- 7 Multi-Objective Circuit Optimization.- 7.1 Introduction.- 7.2 Multiple-Objective Optimization: An Overview.- 7.3 Fuzzy Sets.- 7.4 Multiple-Performance Statistical Optimization.- 7.5 Multiple-Performance Variability Minimization.- 7.6 Summary.- References.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |
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