A Hybrid Method Based on Combining Artificial Neural Network and Fuzzy Inference System for Simultaneous Computation of Resonant Frequencies of Rectangular, Circular, and Triangular Microstrip Antennas
A hybrid method based on a combination of artificial neural network (ANN) and fuzzy inference system (FIS) is presented to calculate simultaneously the resonant frequencies of various microstrip antennas (MSAs) of regular geometries. The ANN is trained with the Bayesian regulation algorithm. An algo...
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| Veröffentlicht in: | IEEE transactions on antennas and propagation Jg. 55; H. 3; S. 659 - 668 |
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| Format: | Journal Article |
| Sprache: | Englisch |
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New York, NY
IEEE
01.03.2007
Institute of Electrical and Electronics Engineers The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
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| ISSN: | 0018-926X, 1558-2221 |
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| Abstract | A hybrid method based on a combination of artificial neural network (ANN) and fuzzy inference system (FIS) is presented to calculate simultaneously the resonant frequencies of various microstrip antennas (MSAs) of regular geometries. The ANN is trained with the Bayesian regulation algorithm. An algorithm that integrates least square method and backpropagation algorithm is used to identify the parameters of FIS. The resonant frequency results of the proposed hybrid method for the rectangular, circular, and triangular MSAs are in very good agreement with the experimental results available in the literature |
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| AbstractList | A hybrid method based on a combination of artificial neural network (ANN) and fuzzy inference system (FIS) is presented to calculate simultaneously the resonant frequencies of various microstrip antennas (MSAs) of regular geometries. The ANN is trained with the Bayesian regulation algorithm. An algorithm that integrates least square method and backpropagation algorithm is used to identify the parameters of FIS. The resonant frequency results of the proposed hybrid method for the rectangular, circular, and triangular MSAs are in very good agreement with the experimental results available in the literature A hybrid method based on a combination of artificial neural network (ANN) and fuzzy inference system (FIS) is presented to calculate simultaneously the resonant frequencies of various microstrip antennas (MSAs) of regular geometries. The ANN is trained with the Bayesian regulation algorithm. An algorithm that integrates least square method and backpropagation algorithm is used to identify the parameters of FIS. The resonant frequency results of the proposed hybrid method for the rectangular, circular, and triangular MSAs are in very good agreement with the experimental results available in the literature. |
| Author | Sarikaya, N. Guney, K. |
| Author_xml | – sequence: 1 givenname: K. surname: Guney fullname: Guney, K. organization: Dept. of Electron. Eng., Erciyes Univ., Kayseri – sequence: 2 givenname: N. surname: Sarikaya fullname: Sarikaya, N. |
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| Keywords | Fuzzy inference system Backpropagation algorithm Fuzzy system Least squares method Resonance frequency Microstrip antennas microstrip antenna (MSA) resonant frequency Neural network Fuzzy neural nets |
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| SubjectTerms | Algorithms Antennas Applied sciences Artificial neural networks Backpropagation algorithms Bayesian methods Computer networks Exact sciences and technology Fuzzy Fuzzy inference system Fuzzy logic Fuzzy neural networks Fuzzy set theory Fuzzy systems Geometry Inference Inference algorithms Learning theory microstrip antenna (MSA) Microstrip antennas neural network Neural networks Radiocommunications Resonant frequencies Resonant frequency Telecommunications Telecommunications and information theory |
| Title | A Hybrid Method Based on Combining Artificial Neural Network and Fuzzy Inference System for Simultaneous Computation of Resonant Frequencies of Rectangular, Circular, and Triangular Microstrip Antennas |
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