Polynomial Chaos Simulation of Analog and Mixed-Signal Systems : Theory, Modeling Method, Application

Lovett, Teems

ISBN 10: 3838353854 / ISBN 13: 9783838353852

Published by LAP LAMBERT Academic Publishing, 2010

About this Item

Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Modeling and simulation have proved over the years to provide insight into system behavior and design. Traditionally, models are designed to only support deterministic inputs and parameters. This forces the user to provide an exact set of operating conditions to run the simulation. Greater insight into the system''s behavior can be achieved by allowing inputs and parameters to reflect the user''s uncertainty. The Monte Carlo method is a common yet costly approach to generating these desired statistical results. This book introduces an alternative approach by applying polynomial chaos theory to an established circuit modeling method. This results in a general uncertainty-based modeling and simulation framework which yields full system statistics after one simulation run. Linear and non- linear systems are discussed using examples from basic circuits to power converters complete with closed-loop control systems. This book will be useful to anyone interested in modeling and simulation, advanced numerical methods or uncertainty propagation.

Seller Inventory # 7398224/2

Bibliographic Details

• Title: Polynomial Chaos Simulation of Analog and Mixed-Signal Systems : Theory, Modeling Method, Application
• Publisher: LAP LAMBERT Academic Publishing
• Publication Date: 2010
• Language: English
• ISBN 10: 3838353854
• ISBN 13: 9783838353852
• Binding: Soft cover
• Condition: Sehr gut
• Seller catalogs:
  • Bücher

About this title

Synopsis

Modeling and simulation have proved over the years to provide insight into system behavior and design. Traditionally, models are designed to only support deterministic inputs and parameters. This forces the user to provide an exact set of operating conditions to run the simulation. Greater insight into the system's behavior can be achieved by allowing inputs and parameters to reflect the user's uncertainty. The Monte Carlo method is a common yet costly approach to generating these desired statistical results. This book introduces an alternative approach by applying polynomial chaos theory to an established circuit modeling method. This results in a general uncertainty-based modeling and simulation framework which yields full system statistics after one simulation run. Linear and non- linear systems are discussed using examples from basic circuits to power converters complete with closed-loop control systems. This book will be useful to anyone interested in modeling and simulation, advanced numerical methods or uncertainty propagation.