Soft computing techniques on multiresonant antenna synthesis and analysis

Abstract

The synthesis and analysis of a multiresonant microstrip patch antenna using soft computing techniques are presented. The multiresonance is obtained via attaching inverted L-shaped stubs to the radiated edges of the single frequency patch antenna. The physical geometry of the proposed antenna is synthesized using adaptive-neuro-fuzzy inference systems and the calculated dimensions are applied to the artificial neural network for the analysis process. The return loss and phase of the scattering parameters are computed. The modeled antenna provides 95% accuracy and sufficient results compared with the simulation and measurement results.

E- and H-shaped high gain patch antennas

“…A very close resonance frequency compared to this work (12.06 GHz) is achieved in a tri‐band MPA with high gain at 9.5, 10.6, and 12.6 GHz is in . Soft computing techniques on multiresonant patch antenna are synthesized and analyzed in , which reduces simulation times using neuro‐fuzzy inference systems and Artificial Neural Networks. In this article, configurations derived from the E‐shape and H‐shape designs that can be used for gain enhancement.…”

Triangular Ring Patch Antenna Analysis: Neuro-Fuzzy Model for Estimating of the Operating Frequency

“…In addition, these approaches require a new solution for every small change in the patch geometry [4]. For this reason, artificial intelligence techniques are widely preferred as more accurate and faster alternative methods in order to overcome these difficulties of traditional techniques in the analysis process of PAs [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18]. The precise mathematical formulations in complex methods involve a large number of numerical operations that result in rounding errors and may require experimental adjustments to theoretical results.…”

“…Artificial intelligence models such as Artificial Neural Network (ANN) [19], Fuzzy Logic (FL) [20], Support Vector Machine (SVM) [20], and Neuro-Fuzzy (NF) [22] eliminate the complex mathematical procedures and time consuming for processes of antenna design. These models have been used extensively for the analysis of various PAs in the literature [5][6][7][8][9][10][11][12][13][14][15][16][17]. In [5][6][7][8][9][10][11][12][13][14][15][16][17], analysis studies were carried out to determine some performance parameters of PAs having various shapes with artificial intelligence techniques such as ANN, SVM, and NF.…”

Slot Parameter Optimization for Multiband Antenna Performance Improvement Using Intelligent Systems

“…The reference geometry [16] has multiband radiation with limited bandwidth capabilities for the interested frequencies. The multiband property is introduced using inverted L shaped stubs to the main patch.…”

“…Bioinspired nature of these techniques allows the microwave equipment designers to avoid repetitive cost of electromagnetic (EM) simulations, manufacturing and test procedures. Artificial neural network (ANN) techniques are well-proven methods for microwave design field including antennas [16], arrays [17], MOSFETs [18], passive components [19], and power amplifiers [20].…”