Randy L. Haupt, Derek Linden

Genetic Algorithms in Electromagnetics

• Gebundenes Buch

Produktbeschreibung

Genetic algorithms have become very important in many fields. Genetic Algorithms in Electromagnetics provides a tutorial of the application of genetic algorithms to problems in electromagnetics. It will provide up-to-date developments in genetic algorithms and a review of the many applications to electromagnetics problems. The software included will help readers solve the problems in the book as well as apply it to their own problems.

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A thorough and insightful introduction to using genetic algorithms to optimize electromagnetic systems

Genetic Algorithms in Electromagnetics focuses on optimizing the objective function when a computer algorithm, analytical model, or experimental result describes the performance of an electromagnetic system. It offers expert guidance to optimizing electromagnetic systems using genetic algorithms (GA), which have proven to be tenacious in finding optimal results where traditional techniques fail.

Genetic Algorithms in Electromagnetics begins with an introduction to optimization and several commonly used numerical optimization routines, and goes on to feature:
_ Introductions to GA in both binary and continuous variable forms, complete with examples of MATLAB(r) commands
_ Two step-by-step examples of optimizing antenna arrays as well as a comprehensive overview of applications of GA to antenna array design problems
_ Coverage of GA as an adaptive algorithm, including adaptive and smart arrays as well as adaptive reflectors and crossed dipoles
_ Explanations of the optimization of several different wire antennas, starting with the famous "crooked monopole"
_ How to optimize horn, reflector, and microstrip patch antennas, which require significantly more computing power than wire antennas
_ Coverage of GA optimization of scattering, including scattering from frequency selective surfaces and electromagnetic band gap materials
_ Ideas on operator and parameter selection for a GA
_ Detailed explanations of particle swarm optimization and multiple objective optimization
_ An appendix of MATLAB code for experimentation

Produktdetails

• Verlag: Wiley & Sons
• 1. Auflage
• Seitenzahl: 320
• Erscheinungstermin: 1. März 2007
• Englisch
• Abmessung: 240mm x 161mm x 22mm
• Gewicht: 590g
• ISBN-13: 9780471488897
• ISBN-10: 0471488895
• Artikelnr.: 20801064

Autorenporträt

Randy L. Haupt, PhD, is a senior scientist in the Applied Research Laboratory at The Pennsylvania State University. Douglas H. Werner, PhD, is a professor of electrical engineering, a senior scientist in the Applied Research Laboratory, and a faculty member of the Materials Research Institute at The Pennsylvania State University.

Inhaltsangabe

Preface. Acknowledgments. 1. Introduction to Optimization in
Electromagnetics. 1.1 Optimizing a Function of One Variable. 1.1.1
Exhaustive Search. 1.1.2 Random Search. 1.1.3 Golden Search. 1.1.4 Newton's
Method. 1.1.5 Quadratic Interpolation. 1.2 Optimizing a Function of
Multiple Variables. 1.2.1 Random Search. 1.2.2 Line Search. 1.2.3
Nelder-Mead Downhill Simplex Algorithm. 1.3 Comparing Local Numerical
Optimization Algorithms. 1.4 Simulated Annealing. 1.5 Genetic Algorithm. 2.
Anatomy of a Genetic Algorithm. 2.1 Creating an Initial Population. 2.2
Evaluating Fitness. 2.3 Natural Selection. 2.4 Mate Selection. 2.4.1
Roulette Wheel Selection. 2.4.2 Tournament Selection. 2.5 Generating
Offspring. 2.6 Mutation. 2.7 Terminating the Run. 3. Step-by-Step Examples.
3.1 Placing Nulls. 3.2 Thinned Arrays. 4. Optimizing Antenna Arrays. 4.1
Optimizing Array Amplitude Tapers. 4.2 Optimizing Array Phase Tapers. 4.2.1
Optimum Quantized Low-Sidelobe Phase Tapers. 4.2.2 Phase-Only Array
Synthesis Using Adaptive GAs. 4.3 Optimizing Arrays with Complex Weighting.
4.3.1 Shaped-Beam Synthesis. 4.3.2 Creating a Plane Wave in the Near Field.
4.4 Optimizing Array Element Spacing. 4.4.1 Thinned Arrays. 4.4.2
Interleaved Thinned Linear Arrays. 4.4.3 Array Element Perturbation. 4.4.4
Aperiodic Fractile Arrays. 4.4.5 Fractal-Random and Polyfractal Arrays.
4.4.6 Aperiodic Refl ectarrays. 4.5 Optimizing Conformal Arrays. 4.6
Optimizing Reconfi gurable Apertures. 4.6.1 Planar Reconfi gurable
Cylindrical Wire Antenna Design. 4.6.2 Planar Reconfi gurable Ribbon
Antenna Design. 4.6.3 Design of Volumetric Reconfi gurable Antennas. 4.6.4
Simulation Results--Planar Reconfi gurable Cylindrical Wire Antenna. 4.6.5
Simulation Results--Volumetric Reconfi gurable Cylindrical Wire Antenna.
4.6.6 Simulation Results--Planar Reconfi gurable Ribbon Antenna. 5. Smart
Antennas Using a GA. 5.1 Amplitude and Phase Adaptive Nulling. 5.2
Phase-Only Adaptive Nulling. 5.3 Adaptive Reflector. 5.4 Adaptive Crossed
Dipoles. 6. Genetic Algorithm Optimization of Wire Antennas. 6.1
Introduction. 6.2 GA Design of Electrically Loaded Wire Antennas. 6.3 GA
Design of Three-Dimensional Crooked-Wire Antennas. 6.4 GA Design of Planar
Crooked-Wire and Meander-Line Antennas. 6.5 GA Design of Yagi-Uda Antennas.
7. Optimization of Aperture Antennas. 7.1 Refl ector Antennas. 7.2 Horn
Antennas. 7.3 Microstrip Antennas. 8. Optimization of Scattering. 8.1
Scattering from an Array of Strips. 8.2 Scattering from Frequency-Selective
Surfaces. 8.2.1 Optimization of FSS Filters. 8.2.2 Optimization of Reconfi
gurable FSSs. 8.2.3 Optimization of EBGs. 8.3 Scattering from Absorbers.
8.3.1 Conical or Wedge Absorber Optimization. 8.3.2 Multilayer Dielectric
Broadband Absorber Optimization. 8.3.3 Ultrathin Narrowband Absorber
Optimization. 9. GA Extensions. 9.1 Selecting Population Size and Mutation
Rate. 9.2 Particle Swarm Optimization (PSO). 9.3 Multiple-Objective
Optimization. 9.3.1 Introduction. 9.3.2 Strength Pareto Evolutionary
Algorithm--Strength Value Calculation. 9.3.3 Strength Pareto Evolutionary
Algorithm--Pareto Set Clustering. 9.3.4 Strength Pareto Evolutionary
Algorithm--Implementation. 9.3.5 SPEA-Optimized Planar Arrays. 9.3.6
SPEA-Optimized Planar Polyfractal Arrays. Appendix: MATLAB(r) Code.
Bibliography. Index.

Rezensionen

"...a boon to senior and graduate engineering students who have to complete a design project." ( CHOICE , September 2007)