https://scholars.lib.ntu.edu.tw/handle/123456789/332440
標題: | Application of evolutionary algorithms and neural network concepts to the design of low-cost, wideband antenna arrays | 作者: | TIAN-LI YU Santarelli S.G Mailloux R.J Roberts T.M Champion M.H Goldberg D.E. |
關鍵字: | Classification; Competent genetic algorithm; Genetic algorithm; Optimization algorithm; Wideband array | 公開日期: | 2007 | 卷: | 6563 | 來源出版物: | Proceedings of SPIE - The International Society for Optical Engineering | 摘要: | This paper describes the application of biologically-inspired algorithms and concepts to the design of wideband antenna arrays In particular, we address two specific design problems. The first involves the design of a constrained-feed network for a Rotman-lens beamformer. We implemented two evolutionary optimization (EO) approaches namely a simple genetic algorithm (SGA) and a competent genetic algorithm. We conducted simulations based on experimental data, which effectively demonstrate that the competent GA outperforms the SGA (i.e., finds a better design solution) as the objective function becomes less specific and more "general." The second design problem involves the implementation of polyomino-shaped subarrays for sidelobe suppression of large, wideband planar arrays. We use a modified screen-saver code to generate random polyomino tilings. A separate code assigns array values to each element of the tiling (i.e., amplitude, phase, time delay, etc.) and computes the corresponding far-field radiation pattern In order to conduct a statistical analysis of pattern characteristics vs. tiling geometry, we needed a way to measure the "similarity" between two arbitrary tilings to ensure that our sampling of the tiling space was somewhat uniformly distnbuted. We ultimately borrowed a concept from neural network theory, which we refer to as the "dot-product metric," to effectively categorize tilings based on their degree of similarity. |
URI: | http://www.scopus.com/inward/record.url?eid=2-s2.0-35948932685&partnerID=MN8TOARS http://scholars.lib.ntu.edu.tw/handle/123456789/332440 |
ISSN: | 0277786X | DOI: | 10.1117/12.724968 | SDG/關鍵字: | Broadband networks; Classification (of information); Constrained optimization; Genetic algorithms; Neural networks; Random access storage; Competent genetic algorithms; Evolutionary optimization (EO); Optimization algorithms; Wideband arrays; Antenna arrays |
顯示於: | 電機工程學系 |
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