Optimization of physics-based equivalent circuits for microstrip patch antennas

Chiu, Tang-Jung; Kuo, Yi-Ting; Chao, Hsueh-Yung; Li, Yiming

doi:10.1109/aps.2007.4396866

Cited by 3 publications

(3 citation statements)

References 4 publications

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“…RBF is tested with 100 samples frequencies but trained only for particular 20 samples frequencies. For ANN calculation by RBF, differ-differ values arrange as target from literature and experimental data [6][7][8][9]. Calculated values of extra ordinary propagation constant of microstrip rectangular patch antenna with GA program are compared with neural analysis results ( fig.…”

Section: Results and Calculationsmentioning

confidence: 99%

“…5) which are in good agreement. This curve is plotted at 1550 Oe for LiTiZn-ferrite slab at SSPL Timarpur Delhi, on which microstrip patch antenna has been designed [6][7][8][9][10][11][12][13][14][15][16].…”

Section: Results and Calculationsmentioning

confidence: 99%

“…Present analysis also incorporate the dispersion effects due to magnetic field biasing in the form of effective propagation constant (Ke) which is not discussed in the referenced articles. Some similar referenced works [7][8][9][10][11] also have done mathematically or by conventional methods for optimization but this technique is rather precise, accurate and sensitive to optimize parameters of patch antenna as well as other type of antenna also. There are many optimization techniques frequently using for the same work.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

GA Analysis of Switchability of Ferrite Rectangular Patch Antenna

Saxena¹,

Verma²,

Pourush³

et al. 2017

IOSR JCE

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The application of Genetic Algorithm (GA) to analyze / optimize the switching behavior of magnetically biased switchable microstrip antenna, fabricated on ferrite substrate, is reported. In this work, GA has been applied to optimize extraordinary wave propagation constant (K e) which is mainly responsible for the switchability of antenna. The wave propagation constant becomes zero or negative under proper magnetic biasing which resist the antenna as radiator without a mechanical maneuvering. The fitness functions for the GA program have been developed using mathematical formulation based on nonreciprocal approach of ferrite substrate under external magnetic field. The computed results are in good agreement with the results obtained experimentally and trained artificial neural network analysis. In this ANN training Radial Basis Function (RBF) networks is used. All programming related to genetic algorithm and ANN analysis performed by MatLab 7.1.

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Section: Results and Calculationsmentioning

confidence: 99%

Section: Results and Calculationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

GA Analysis of Switchability of Ferrite Rectangular Patch Antenna

Saxena¹,

Verma²,

Pourush³

et al. 2017

IOSR JCE

View full text Add to dashboard Cite

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Cavity model surrogate-based optimization for electrically thick circularly polarized rectangular microstrip antennas

Mona

Sakomura

Nascimento

2021

AEU - International Journal of Electronics and Communications

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Application of Genetic Algorithm for Optimization of Important Parameters of Magnetically Biased Microstrip Circular Patch Antenna

Saxena¹,

Khan²,

Kumar³

et al. 2011

JSEA

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The application of Genetic Algorithm (GA) to the optimization of important parameters (Directivity, Radiated Power, Impedance etc.) of magnetically biased microstrip antenna, fabricated on ferrite substrate, is reported. The fitness functions for the GA program have been developed using cavity method for the analysis of microstrip antenna. The effect of external magnetic biasing has also been incorporated in the fitness function formulation as effective propagation constant. Using stochastic based search method of GA the common characteristics of electro-magnetic were entertained which cannot be handled by other optimization techniques. The genetic algorithm was run for 500 generations. The computed results are in good agreement with the results obtained experimentally

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Optimization of physics-based equivalent circuits for microstrip patch antennas

Cited by 3 publications

References 4 publications

GA Analysis of Switchability of Ferrite Rectangular Patch Antenna

GA Analysis of Switchability of Ferrite Rectangular Patch Antenna

Cavity model surrogate-based optimization for electrically thick circularly polarized rectangular microstrip antennas

Application of Genetic Algorithm for Optimization of Important Parameters of Magnetically Biased Microstrip Circular Patch Antenna

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