Electronic Design Automation of Analog ICs combining Gradient Models with Multi-Objective Evolutionary Algorithms, Frederico A.E. Rocha; Ricardo M.F. Martins; Nuno C
Автор: Martins Название: Analog Integrated Circuit Design Automation ISBN: 331934059X ISBN-13(EAN): 9783319340593 Издательство: Springer Рейтинг: Цена: 107130.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces readers to a variety of tools for analog layout design automation. After discussing the placement and routing problem in electronic design automation (EDA), the authors overview a variety of automatic layout generation tools, as well as the most recent advances in analog layout-aware circuit sizing. The discussion includes different methods for automatic placement (a template-based Placer and an optimization-based Placer), a fully-automatic Router and an empirical-based Parasitic Extractor. The concepts and algorithms of all the modules are thoroughly described, enabling readers to reproduce the methodologies, improve the quality of their designs, or use them as starting point for a new tool. All the methods described are applied to practical examples for a 130nm design process, as well as placement and routing benchmark sets.
Автор: Michael Fulde Название: Variation Aware Analog and Mixed-Signal Circuit Design in Emerging Multi-Gate CMOS Technologies ISBN: 9400730837 ISBN-13(EAN): 9789400730830 Издательство: Springer Цена: 104480.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Preface. Danksagung. 1 Introduction. 1.1 Motivation. 1.2 Scaling Fundamentals. 1.3 Variability from Analog and Mixed-Signal Perspective. 2 Analog Properties of Multi-Gate MOSFETs. 2.1 Introduction to Recent FinFET Technology. 2.2 DC Characteristics. 2.3 Analog and RF Characteristics. 2.4 Matching Behavior. 2.5 Charge-Trapping. 2.6 Self-Heating. 3 High-k Related Design Issues. 3.1 Flicker Noise. 3.2 Transient VT Variations and Hysteresis Effects. 4 Multi-Gate Related Design Aspects. 4.1 Biasing Circuits. 4.2 Operational Amplifiers. 4.3 Bandgap Reference Circuits. 4.4 D/A Converter. 4.5 Phase-Locked-Loop Circuit. 4.6 RF Building Blocks. 4.7 Self-Heating. 4.8 Selective Fin Width Tuning. 5 Multi-Gate Tunneling FETs. 5.1 Principle of Operation and Implementation of MuGTFETs. 5.2 Measurement Results. 5.3 Device Simulation. 5.4 MuGTFET Reference Circuit. 6 Conclusions and Outlook. Symbols and Abbreviations. References.
Автор: Michael Fulde Название: Variation Aware Analog and Mixed-Signal Circuit Design in Emerging Multi-Gate CMOS Technologies ISBN: 9048132797 ISBN-13(EAN): 9789048132799 Издательство: Springer Рейтинг: Цена: 130610.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book offers a technology-oriented assessment of analog and mixed-signal circuits in emerging high-k and multi-gate CMOS technologies. Coverage includes transient threshold voltage variations and integration of tunnel transistors in a multi-gage process.
Автор: M.C. Bhuvaneswari Название: Application of Evolutionary Algorithms for Multi-objective Optimization in VLSI and Embedded Systems ISBN: 8132219570 ISBN-13(EAN): 9788132219576 Издательство: Springer Рейтинг: Цена: 130430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book describes how evolutionary algorithms (EA), including genetic algorithms (GA) and particle swarm optimization (PSO) can be utilized for solving multi-objective optimization problems in the area of embedded and VLSI system design.
Автор: Ashish Ghosh; Satchidananda Dehuri; Susmita Ghosh Название: Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases ISBN: 3642096158 ISBN-13(EAN): 9783642096150 Издательство: Springer Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Genetic Algorithm for Optimization of Multiple Objectives in Knowledge Discovery from Large Databases.- Knowledge Incorporation in Multi-objective Evolutionary Algorithms.- Evolutionary Multi-objective Rule Selection for Classification Rule Mining.- Rule Extraction from Compact Pareto-optimal Neural Networks.- On the Usefulness of MOEAs for Getting Compact FRBSs Under Parameter Tuning and Rule Selection.- Classification and Survival Analysis Using Multi-objective Evolutionary Algorithms.- Clustering Based on Genetic Algorithms.
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