Evolutionary Robust Design of Analog Filters Using Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InCollection{hu:2007:ECdue,

• author = "Jianjun Hu and Shaobo Li and Erik D. Goodman",
• title = "Evolutionary Robust Design of Analog Filters Using Genetic Programming",
• booktitle = "Evolutionary Computation in Dynamic and Uncertain Environments",
• publisher = "Springer",
• year = "2007",
• editor = "Shengxiang Yang and Yew-Soon Ong and Yaochu Jin",
• volume = "51",
• series = "Studies in Computational Intelligence",
• pages = "479--496",
• chapter = "21",
• email = "hujianju@gmail.com",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-540-49772-1",
• DOI = "doi:10.1007/978-3-540-49774-5_21",
• abstract = "This chapter proposes a robust design approach that exploits the open ended topological synthesis capability of genetic programming (GP) to evolve robust low pass and high pass analog filters. Compared with a traditional robust design approach based on genetic algorithms (GAs), the open-ended topology search based on genetic programming and bond graph modeling (GPBG) is shown to be able to evolve more robust filters with respect to parameter perturbations than what was achieved through parameter tuning alone, for the test problems.",
• notes = "http://www.cse.sc.edu/~jianjunh/",

}

Genetic Programming entries for Jianjun Hu Shaobo Li Erik Goodman

Citations