Nonlinear Optimization in Electrical Engineering with Applications in MATLAB
- 4h 13m
- Mohamed Bakr
- Institution of Engineering and Technology
- 2013
Nonlinear Optimization in Electrical Engineering with Applications in MATLAB provides an introductory course on nonlinear optimization in electrical engineering, with a focus on applications including the design of electric, microwave and photonic circuits, wireless communications and digital filter design. Basic concepts are introduced using a step-by-step approach featuring a variety of practical electrical engineering-related examples and illustrated with MATLAB codes that the reader can use and adapt. Topics covered include classical optimization methods, one dimensional optimization, unconstrained optimization, constrained optimization, global optimization, space mapping optimization, and adjoint variable methods.
- Basic concepts are introduced using a step-by-step approach
- Features a variety of practical electrical engineering-related examples
- Illustrated with MATLAB® codes that the reader can use and adapt.
- Topics covered include: classical optimization methods, one dimensional optimization, unconstrained optimization, constrained optimization, global optimization, space mapping optimization and adjoint variable methods.
It will be essential reading for advanced students in electrical engineering and will also interest electrical engineering professionals.
About the Author
Mohamed Bakr is an Associate Professor at the Department of Electrical and Computer Engineering, McMaster University, Canada, where his research interests include optimization methods, computer-aided design and modelling of microwave circuits, neural networks applications, smart analysis of microwave circuits and efficient optimization using time domain simulation methods.
In this Book
-
Mathematical Background
-
An Introduction to Linear Programming
-
Classical Optimization
-
One-Dimensional Optimization-Line Search
-
Derivative-Free Unconstrained Techniques
-
First-Order Unconstrained Optimization Techniques
-
Second-Order Unconstrained Optimization Techniques
-
Constrained Optimization Techniques
-
Introduction to Global Optimization Techniques
-
Adjoint Sensitivity Analysis
