Design of multiple function antenna array using radial basis function neural network

Reddy, B. Rama Sanjeeva; Vakula, D.; Sarma, N. V. S. N.

doi:10.1590/s2179-10742013000100016

Cited by 4 publications

(1 citation statement)

References 6 publications

(5 reference statements)

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“…Other methods based on machine learning have been shown to simplify the electromagnetic calculations and to approximate with great accuracy the electronic performances of coupled, decoupled, periodic, and aperiodic arrays [19][20][21][22][23][24][25][26][27][28][29][30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

Radiation Pattern Synthesis of the Coupled almost Periodic Antenna Arrays Using an Artificial Neural Network Model

Hamdi

Aguili

2022

Electronics

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This paper proposes radiation pattern synthesis of almost periodic antenna arrays including mutual coupling effects (extracted by Floquet analysis according to our previous work), which in principal has high directivity and a large bandwidth. For modeling the given structures, the moment method combined with the generalized equivalent circuit (MoM-GEC) is proposed. The artificial neural network (ANN), as a powerful computational model, has been successfully applied to antenna array pattern synthesis. Our results showed that multilayer feedforward neural networks are rugged and can successfully and efficiently resolve various distinctive, complex almost periodic antenna patterns (with different source amplitudes) (in particular, both periodic and randomly aperiodic structures are taken into account). An ANN is capable of quickly producing the synthesis results using generalization with the early stopping (ES) method. Significant advantages in speed and memory consumption are achieved by using this method to improve the generalization (called early stopping). To justify this work, several examples are shown and discussed.

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Section: Introductionmentioning

confidence: 99%

Radiation Pattern Synthesis of the Coupled almost Periodic Antenna Arrays Using an Artificial Neural Network Model

Hamdi

Aguili

2022

Electronics

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Efficient yield estimation of multiband patch antennas by polynomial chaos‐based Kriging

Leifsson

Koziel

2020

Int J Numerical Modelling

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Yield estimation of antenna systems is important to check their robustness with respect to the uncertain sources. Since direct Monte Carlo sampling of accurate physics-based models can be computationally intensive, this work proposes the use of the polynomial chaos-Kriging (PC-Kriging) metamodeling method for fast yield estimation of multiband patch antennas. PC-Kriging integrates the polynomial chaos expansion (PCE) as the trend function of Kriging metamodel since the PCE is good at capturing the function tendency and Kriging is good at matching the observations at training points. The PC-Kriging method is demonstrated on two analytical cases and two multiband patch antenna cases and is compared with the PCE and Kriging metamodeling methods. In the analytical cases, PC-Kriging reduces the computational cost by over 40% compared with PCE and over 94% compared with Kriging. In the antenna cases, PC-Kriging reduces the computational cost by over 60% compared with Kriging and over 90% compared with PCE. In all cases, the savings are obtained without compromising the accuracy. K E Y W O R D S antenna yield estimation, Kriging, microstrip multiband patch antenna, Monte Carlo sampling, polynomial chaos expansions, polynomial chaos-based Kriging

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Rapid Multi-band Patch Antenna Yield Estimation Using Polynomial Chaos-Kriging

Leifsson

Kozieł

2019

Lecture Notes in Computer Science

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Design of multiple function antenna array using radial basis function neural network

Cited by 4 publications

References 6 publications

Radiation Pattern Synthesis of the Coupled almost Periodic Antenna Arrays Using an Artificial Neural Network Model

Radiation Pattern Synthesis of the Coupled almost Periodic Antenna Arrays Using an Artificial Neural Network Model

Efficient yield estimation of multiband patch antennas by polynomial chaos‐based Kriging

Rapid Multi-band Patch Antenna Yield Estimation Using Polynomial Chaos-Kriging

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