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Titlebook: Genetic Algorithms for Control and Signal Processing; Kim F. Man,Kit S. Tang,Wolfgang A. Halang Book 1997 Springer-Verlag London Limited 1

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发表于 2025-3-21 18:36:08 | 显示全部楼层 |阅读模式
书目名称Genetic Algorithms for Control and Signal Processing
编辑Kim F. Man,Kit S. Tang,Wolfgang A. Halang
视频videohttp://file.papertrans.cn/383/382440/382440.mp4
丛书名称Advances in Industrial Control
图书封面Titlebook: Genetic Algorithms for Control and Signal Processing;  Kim F. Man,Kit S. Tang,Wolfgang A. Halang Book 1997 Springer-Verlag London Limited 1
描述The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies, . . . , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. The emerging technologies in control include fuzzy logic, intelligent control, neural networks and hardware developments like micro-electro-mechanical systems and autonomous vehicles. This volume describes the biological background, basic construction and application of the emerging technology of Genetic Algorithms. Dr Kim Man and his colleagues have written a book which is both a primer introducing the basic concepts and a research text which describes some of the more advanced applications of the genetic algorithmic method. T
出版日期Book 1997
关键词algorithm; control; filter design; neural networks; optimization; signal processing
版次1
doihttps://doi.org/10.1007/978-1-4471-0955-6
isbn_softcover978-1-4471-1241-9
isbn_ebook978-1-4471-0955-6Series ISSN 1430-9491 Series E-ISSN 2193-1577
issn_series 1430-9491
copyrightSpringer-Verlag London Limited 1997
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https://doi.org/10.1007/b137847tion is the optimal low order weighting functions for the design of H. control, using the Loop Shaping Design Procedure (LSDP). Here a detailed account for both design methods is presented, and the essences of applying the HGA as a topological optimizer are accurately described.
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Modification in Genetic Algorithm,ng and conflicting. Therefore, a means of modifying the GA structure is sought in order to meet the design requirements. There are many facets of operational modes that can be introduced. It is the main task of this chapter to outline the essential methodologies.
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Filtering Optimization,tion is the optimal low order weighting functions for the design of H. control, using the Loop Shaping Design Procedure (LSDP). Here a detailed account for both design methods is presented, and the essences of applying the HGA as a topological optimizer are accurately described.
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Vasilios K. Thomaidis MD, DDS, PhDe, the purpose of this chapter is to consider three special case studies in which the main features of the GA are outlined. It is also hoped that the advantages of using GA for engineering designs can be highlighted and used as a reference for designing future systems.
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Advanced GA Applications,e, the purpose of this chapter is to consider three special case studies in which the main features of the GA are outlined. It is also hoped that the advantages of using GA for engineering designs can be highlighted and used as a reference for designing future systems.
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