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This book focuses on optimal control and systems engineering in the
big data era. It examines the scientific innovations in
optimization, control and resilience management that can be applied
to further success. In both business operations and engineering
applications, there are huge amounts of data that can overwhelm
computing resources of large-scale systems. This "big data"
provides new opportunities to improve decision making and addresses
risk for individuals as well in organizations. While utilizing data
smartly can enhance decision making, how to use and incorporate
data into the decision making framework remains a challenging
topic. Ultimately the chapters in this book present new models and
frameworks to help overcome this obstacle. Optimization and Control
for Systems in the Big-Data Era: Theory and Applications is divided
into five parts. Part I offers reviews on optimization and control
theories, and Part II examines the optimization and control
applications. Part III provides novel insights and new findings in
the area of financial optimization analysis. The chapters in Part
IV deal with operations analysis, covering flow-shop operations and
quick response systems. The book concludes with final remarks and a
look to the future of big data related optimization and control
problems.
This book focuses on optimal control and systems engineering in the
big data era. It examines the scientific innovations in
optimization, control and resilience management that can be applied
to further success. In both business operations and engineering
applications, there are huge amounts of data that can overwhelm
computing resources of large-scale systems. This "big data"
provides new opportunities to improve decision making and addresses
risk for individuals as well in organizations. While utilizing data
smartly can enhance decision making, how to use and incorporate
data into the decision making framework remains a challenging
topic. Ultimately the chapters in this book present new models and
frameworks to help overcome this obstacle. Optimization and Control
for Systems in the Big-Data Era: Theory and Applications is divided
into five parts. Part I offers reviews on optimization and control
theories, and Part II examines the optimization and control
applications. Part III provides novel insights and new findings in
the area of financial optimization analysis. The chapters in Part
IV deal with operations analysis, covering flow-shop operations and
quick response systems. The book concludes with final remarks and a
look to the future of big data related optimization and control
problems.
This comprehensive compendium describes the basic modeling
techniques for silicon-based semiconductor devices, introduces the
basic concepts of silicon-based passive and active devices, and
provides its state-of-the-art modeling and equivalent circuit
parameter extraction methods.The unique reference text benefits
practicing engineers, technicians, senior undergraduate and
first-year graduate students working in the areas of RF, microwave
and solid-state device, and integrated circuit design.
A highly comprehensive summary on circuit related modeling
techniques and parameter extraction methods for heterojunction
bipolar transistors Heterojunction Bipolar Transistor (HBT) is one
of the most important devices for microwave applications. The book
details the accurate device modeling for HBTs and high level IC
design using HBTs Provides a valuable reference to basic modeling
issues and specific semiconductor device models encountered in
circuit simulators, with a thorough reference list at the end of
each chapter for onward learning Offers an overview on modeling
techniques and parameter extraction methods for heterojunction
bipolar transistors focusing on circuit simulation and design
Presents electrical/RF engineering-related theory and tools and
include equivalent circuits and their matrix descriptions, noise,
small and large signal analysis methods
This book is an introduction to microwave and RF signal modeling
and measurement techniques for field effect transistors. It assumes
only a basic course in electronic circuits and prerequisite
knowledge for readers to apply the techniques and improve the
performance of integrated circuits, reduce design cycles and
increase their chance at first time success. The first chapters
offer a general overview and discussion of microwave signal and
noise matrices, and microwave measurement techniques. The following
chapters address modeling techniques for field effect transistors
and cover models such as: small signal, large signal, noise, and
the artificial neural network based.
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