OPTIMAL MULTILAYER FILTER DESIGN USING REAL CODED GENETIC ALGORITHMS

被引:53
作者
MICHIELSSEN, E [1 ]
RANJITHAN, S [1 ]
MITTRA, R [1 ]
机构
[1] UNIV ILLINOIS,DEPT CIVIL ENGN,URBANA,IL 61801
来源
IEE PROCEEDINGS-J OPTOELECTRONICS | 1992年 / 139卷 / 06期
关键词
GENETIC ALGORITHMS; MULTILAYER FILTERS;
D O I
10.1049/ip-j.1992.0070
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
A novel approach for designing optimal multilayer filters based on a real-coded genetic algorithm is presented. Given the total number of layers in the filter, as well as the electrical properties of the materials constituting each layer, the algorithm iteratively constructs multilayers whose frequency response closely matches a desired frequency response. In contrast to existing iterative techniques, this method does not require a preliminary design using classical techniques. Also, the design procedure is independent of the nature of the multilayer as well as the characteristics of the incident and substrate media. The algorithm is applied to the design of various lowpass and high-pass optical filters, operating between practical terminal conditions. The performance of the resulting designs matches or improves on that for filters that were synthesised using semiclassical techniques.
引用
收藏
页码:413 / 420
页数:8
相关论文
共 50 条
  • [21] Design and optimization of IIR filter structure using hierarchical genetic algorithms
    Tang, KS
    Man, KF
    Kwong, S
    Liu, ZF
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 1998, 45 (03) : 481 - 487
  • [22] AN OPTIMAL EXTENDED KALMAN FILTER DESIGNED BY GENETIC ALGORITHMS
    Rezaei, N.
    Kordabadi, H.
    Elkamel, A.
    Jahanmiri, A.
    CHEMICAL ENGINEERING COMMUNICATIONS, 2009, 196 (05) : 602 - 615
  • [23] Optimization of multimodal continuous functions using a new crossover for the real-coded genetic algorithms
    Tutkun, Nedim
    EXPERT SYSTEMS WITH APPLICATIONS, 2009, 36 (04) : 8172 - 8177
  • [24] The use of genetic algorithms in morphological filter design
    Harvey, NR
    Marshall, S
    SIGNAL PROCESSING-IMAGE COMMUNICATION, 1996, 8 (01) : 55 - 71
  • [25] Filter selection using genetic algorithms
    Patel, D
    APPLICATIONS OF ARTIFICIAL NEURAL NETWORKS IN IMAGE PROCESSING, 1996, 2664 : 95 - 102
  • [26] An improved class of real-coded Genetic Algorithms for numerical optimization
    Ali, Mostafa Z.
    Awad, Noor H.
    Suganthan, Ponnuthurai N.
    Shatnawi, Ali M.
    Reynolds, Robert G.
    NEUROCOMPUTING, 2018, 275 : 155 - 166
  • [27] Probabilistic Fitting of Glucose Models with Real-Coded Genetic Algorithms
    Cervigon, Carlos
    Manuel Velasco, J.
    Burgos-Simon, Clara
    Villanueva, Rafael J.
    Ignacio Hidalgo, J.
    2021 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC 2021), 2021, : 736 - 743
  • [28] An Optimal Design Methodology of Tapered Roller Bearings Using Genetic Algorithms
    Tiwari, Rajiv
    Sunil, Kumar K.
    Reddy, R. S.
    INTERNATIONAL JOURNAL FOR COMPUTATIONAL METHODS IN ENGINEERING SCIENCE & MECHANICS, 2012, 13 (02) : 108 - 127
  • [29] Design of optimal disturbance rejection PID controllers using genetic algorithms
    Krohling, RA
    Rey, JP
    IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2001, 5 (01) : 78 - 82
  • [30] Optimal design method for building energy systems using genetic algorithms
    Ooka, Ryozo
    Komamura, Kazuhiko
    BUILDING AND ENVIRONMENT, 2009, 44 (07) : 1538 - 1544