| 000 | 08098nam a2200937 i 4500 | ||
|---|---|---|---|
| 001 | 5237622 | ||
| 003 | IEEE | ||
| 005 | 20220712205616.0 | ||
| 006 | m o d | ||
| 007 | cr |n||||||||| | ||
| 008 | 070425t20152007njua ob 001 0 eng d | ||
| 020 |
_a9780470106280 _qelectronic |
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| 020 |
_z9780471488897 _qpaper |
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| 020 |
_z047010628X _qelectronic |
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| 024 | 7 |
_a10.1002/047010628X _2doi |
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| 035 | _a(CaBNVSL)mat05237622 | ||
| 035 | _a(IDAMS)0b00006481095a22 | ||
| 040 |
_aCaBNVSL _beng _erda _cCaBNVSL _dCaBNVSL |
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| 050 | 4 |
_aTK7871.6 _b.H37 2007eb |
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| 082 | 0 | 4 |
_a621.30285/631 _222 |
| 100 | 1 |
_aHaupt, Randy L. _eauthor. _926477 |
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| 245 | 1 | 0 |
_aGenetic algorithms in electromagnetics / _cRandy L. Haupt, Douglas H. Werner. |
| 264 | 1 |
_aHoboken, New Jersey : _bIEEE Press : _cc2007. |
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| 300 |
_a1 PDF (xiii, 301 pages) : _billustrations. |
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| 336 |
_atext _2rdacontent |
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| 337 |
_aelectronic _2isbdmedia |
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| 338 |
_aonline resource _2rdacarrier |
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| 504 | _aIncludes bibliographical references (p. 277-297) and index. | ||
| 505 | 0 | _aPreface. -- 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. | |
| 505 | 8 | _a5.1 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 Yagida 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 Code. -- Bibliography. -- Index. | |
| 506 | 1 | _aRestricted to subscribers or individual electronic text purchasers. | |
| 520 | _aA 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. | ||
| 530 | _aAlso available in print. | ||
| 538 | _aMode of access: World Wide Web. | ||
| 588 | _aDescription based on PDF viewed 12/18/2015. | ||
| 650 | 0 |
_aAntenna arrays _xDesign. _926478 |
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| 650 | 0 |
_aElectromagnetism _xMathematical models. _96379 |
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| 650 | 0 |
_aGenetic algorithms. _93938 |
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| 655 | 0 |
_aElectronic books. _93294 |
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| 695 | _aAdaptive arrays | ||
| 695 | _aAntenna arrays | ||
| 695 | _aAntenna radiation patterns | ||
| 695 | _aAperture antennas | ||
| 695 | _aArrays | ||
| 695 | _aBibliographies | ||
| 695 | _aBiological cells | ||
| 695 | _aBroadband antennas | ||
| 695 | _aComputers | ||
| 695 | _aConvergence | ||
| 695 | _aCost function | ||
| 695 | _aElectromagnetics | ||
| 695 | _aEncoding | ||
| 695 | _aEvolution (biology) | ||
| 695 | _aGallium | ||
| 695 | _aGenerators | ||
| 695 | _aGenetic algorithms | ||
| 695 | _aGenetics | ||
| 695 | _aHorn antennas | ||
| 695 | _aIndexes | ||
| 695 | _aInterference | ||
| 695 | _aLinear antenna arrays | ||
| 695 | _aLoaded antennas | ||
| 695 | _aMATLAB | ||
| 695 | _aMoment methods | ||
| 695 | _aMonitoring | ||
| 695 | _aOptimization | ||
| 695 | _aParticle swarm optimization | ||
| 695 | _aPhase shifters | ||
| 695 | _aPhased arrays | ||
| 695 | _aPolynomials | ||
| 695 | _aPower generation | ||
| 695 | _aScattering | ||
| 695 | _aSignal processing algorithms | ||
| 695 | _aWheels | ||
| 695 | _aWire | ||
| 700 | 1 |
_aWerner, Douglas H., _d1960- _926479 |
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| 710 | 2 |
_aIEEE Xplore (Online service), _edistributor. _926480 |
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| 776 | 0 | 8 |
_iPrint version: _z9780471488897 |
| 856 | 4 | 2 |
_3Abstract with links to resource _uhttps://ieeexplore.ieee.org/xpl/bkabstractplus.jsp?bkn=5237622 |
| 942 | _cEBK | ||
| 999 |
_c73785 _d73785 |
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