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Simulation-Driven Design Optimization And Modeling For Microwave Engineering

SMLTN-DRVN DESIGN OPTIMZATION & MDLNG FOR MICROWAVE ENG

Engineering

Mathematics & Science

Gt Product Group

Binding Format

Marketing Imprint Name

B2B GT

CL Carton Count

Imprint Name

B2B & B2C

Complementary and integrative medicine (CIM) has become big business. Alongside the increased consumption of complementary medicine and the swelling numbers of complementary health practitioners has emerged a growing interest in these medicines and therapies from within the ranks of conventional primary health care. At the level of practice and beyond, a culture of confrontation and antagonism has begun to be replaced by a focus upon potential integration, collaboration and common ground.With these significant developments in mind, this ground-breaking book is a valuable and timely addition to the CIM and primary health care research literature. The collection outlines the core issues, challenges and opportunities facing the CIM-primary health care interface and its study and will provide insight and inspiration for those practising, studying and researching the contemporary relations between CIM and primary health care.

Post Secondary Four Year

College Freshman

College Junior

College Sophomore

College Senior

Duration

Duration Unit Of Measure

Transaction Type

Front Cover.
Half Title Page.
Title Page.
Copyright Page.
List of Contributors.
Preface.
Acknowledgments.
Contents.
1: Introduction to Optimization and Gradient-Based Methods.
2: Derivative-Free Methods and Metaheuristics.
3: Surrogate-Based Optimization.
4: Space Mapping.
5: Tuning Space Mapping.
6: Robust Design Using Knowledge-Based Response Correction and Adaptive Design Specifications.
7: Simulation-Driven Design of Broadband Antennas Using Surrogate-Based Optimization.
8: Neural Networks for Radio Frequency/Microwave Modeling.
9: Parametric Modeling of Microwave Passive Components Using Combined Neural Network and Transfer Function.
10: Parametric Sensitivity Macromodels for Gradient-Based Optimization.
11: Neural Space Mapping Methods for Electromagnetics-Based Yield Estimation.
12: Neural Network Inverse Modeling for Microwave Filter Design.
13: Simulation-Driven Design of Microwave Filters for Space Applications.
14: Time Domain Adjoint Sensitivities: The Transmission Line Modeling (TLM) Case.
15: Boundary Conditions for Two-Dimensional Finite-Element Modeling of Microwave Devices.
16: Boundary Conditions for Three-Dimensional Finite-Element Modeling of Microwave Devices.
Index.

Simulation-Driven Design Optimization And Modeling For Microwave Engineering.css-1p8rvzy{position:absolute;padding-left:8px;}

Simulation-Driven Design Optimization And Modeling For Microwave Engineering