Analysis and synthesis of sierpinski gasket fractal antenna using ANFIS

Gehani, Aarti; Agnihotri, Prashasti; Pujara, Dhaval

doi:10.1109/apusncursinrsm.2017.8072219

Cited by 3 publications

(2 citation statements)

References 6 publications

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“…Multiple fractal geometries have been investigated by different researchers in the last few decades . An ultra‐wideband antenna of size 26 × 21 × 1.6 mm 3 based on Cantor set fractal technology is presented in Reference .…”

Section: Introductionmentioning

confidence: 99%

Giuseppe Peano and Cantor set fractals based miniaturized hybrid fractal antenna for biomedical applications using artificial neural network and firefly algorithm

Kaur

Sivia

2019

Int J RF Microw Comput Aided Eng

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In this research paper, Giuseppe Peano and Cantor set fractals based miniaturized hybrid fractal antenna (GCHFA) is proposed that operates for biomedical applications. The proposed GCHFA is designed by merging Giuseppe Peano and Cantor set fractals that help in achieving better performance characteristics as well as miniaturization. Firefly algorithm (FA) has been employed to optimize the feed position of the designed antenna. The substrate material selected for the proposed GCHFA is low-cost, commercially available FR4 epoxy whose thickness is 1.6 mm and relative permittivity is 4.4. A data set of 65 GCHFAs with different geometrical parameters is generated for the realization of two different bioinspired approaches.For the performance evaluation of fabricated prototype, vector network analyzer is used. The experimentally observed resonant frequencies are 2.4400 and 5.8115 GHz, and at these resonant frequencies, S (1,1) < −10 dB. The designed antenna is suitable for Industrial, Scientific, and Medical bands of biomedical applications. Moreover, the behavior of the proposed GCHFA is nearly omnidirectional. A comparative study of three different artificial neural networks (ANNs) is also done to evaluate the most suitable ANN type for the analysis of proposed GCHFA. The optimized, simulated, and experimental results depict that they are closely matched. K E Y W O R D S artificial neural network, biomedical applications, feed position, firefly algorithm, hybrid fractal antenna, resonant frequency

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Section: Introductionmentioning

confidence: 99%

Giuseppe Peano and Cantor set fractals based miniaturized hybrid fractal antenna for biomedical applications using artificial neural network and firefly algorithm

Kaur

Sivia

2019

Int J RF Microw Comput Aided Eng

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“…It is known that the different fractal models (Sierpinski rug, Mandelbrot set etc. ), describe well the real imperfection (Brownian) surfaces of metal layers, dielectric layers [2], semiconductor surfaces [3], surfaces with the distribution of defects of symmetric type [4,5]. In Refs.…”

Section: Introductionmentioning

confidence: 99%

2D Fractal Models of Textured Polymer Coatings of Steel Sheet

et al. 2019

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Surface roughness plays an important role in many physical phenomena, including wave scattering, friction, adhesion, electrical conductivity, capacitance and heat transfer, as well as applications of thin films for sensors. We studied microphotographies of polyester coatings surfaces of metal sheets, and concluded that they are rough ones. Using the scanning probe microscopy method, we investigated the surface texture of these samples and found that the largest number of peaks on the surface has a height in the range exceeding the roughness level, and their distribution on surfaces has a fractal character. We used the method of 2D fractal functions for modeling of surface texture of these samples. The optimal fractal model was chosen on the basis of comparison of the geometrical profiles for polymer coating surface of metal sheet obtained by the opticale microscopy method and calculated on the basis of fractal models.

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