Modeling and design of printed antennas using neural networks

Tighilt, Yamina; Bouttout, Farid; Khellaf, A.

doi:10.1002/mmce.20509

Cited by 39 publications

(33 citation statements)

References 20 publications

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“…It is important that the surrogate is physically based [10], so that it can give a reliable prediction of the original structure's behavior under the modification of its designable parameters. One of the most successful techniques in microwave engineering exploiting physically based surrogate models is space mapping (SM) [11–20]. SM replaces direct optimization of a CPU‐intensive structure (“fine” model) by iterative optimization and updating of so‐called coarse models that are less accurate but cheaper to evaluate.…”

Section: Introductionmentioning

confidence: 99%

Obstructive uropathy caused by an inguinal hernia in a kidney transplant recipient: Report of hernia cure by the shouldice technique

Tran

Gaboriault

Collette

et al. 2011

Dialysis & Transplantation

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We report the case of kidney graft dysfunction secondary to ureteral obstruction caused by an inguinal hernia. A 52‐year‐old renal transplant recipient was admitted to our transplantation unit for abdominal pain and acute rise in serum creatinine level. Radiological work‐up showed that the distal transplant ureter was trapped in a left inguinal hernia. After placement of a temporary percutaneous nephrostomy tube and hernia repair by the Shouldice technique, the graft function improved and has remained stable at 1 year of follow‐up. Although infrequent, inguinal hernia can be a cause of obstructive uropathy and graft failure in a transplanted kidney, and the Shouldice technique is appropriate for cure of hernia in this setting. Dial. Transplant. © 2011 Wiley Periodicals, Inc.

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Section: Introductionmentioning

confidence: 99%

Obstructive uropathy caused by an inguinal hernia in a kidney transplant recipient: Report of hernia cure by the shouldice technique

Tran

Gaboriault

Collette

et al. 2011

Dialysis & Transplantation

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“…[7] to study arbitrary shaped scatterers, is applied in the analysis of the scattering problem by a set of perfect conducting angular structures using the artificial neural network (ANN). [19][20][21][22][23] The supervised learning with the multilayer feed-forward network architecture is chosen together with The resilient backpropagation known as RPROP algorithm. [24][25][26][27] The main aim of this algorithm is to identify the appropriate electromagnetic coupling operator between each two pixels among all pixels of the discretized surface and to optimize the calculation time for a large huge mesh surface.…”

Section: Introductionmentioning

confidence: 99%

An efficient algorithm for electromagnetic scattering by a set of perfect conducting cylindrical objects using the artificial neural network

Ines¹,

Ammar²,

Aguili³

et al. 2018

Int J RF Microw Comput Aided Eng

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In this article an efficient algorithm based on the wave concept iterative process is formulated and applied in order to investigate the electromagnetic scattering by a set of conducting arbitrarily shaped objects placed in the free space. In this approach, the cylindrical coordinates system is used as a modal base in order to develop the modal coefficients of the diffraction operator. This operator models the reaction of the environment expressing the electromagnetic coupling between each two pixels of the discretized surface. A study of electromagnetic coupling between two pixels positioned and oriented somehow in the free space is highlighted so as to determine the coupling operator for different positions and orientations of the emitted and received waves. Twelve coupling operators are developed. For a complex geometric shape structure, the determination of these characteristics involved the determination of interactions between each pixel and the others that constitute the discretized surface. This interaction involves the wave formulation already highlighted for each couple of pixels which implies a higher calculation time. In order to optimize the calculation time, the artificial neural networks are adopted with the feed‐forward architecture. The supervised learning has been chosen with the use of the resilient backpropagation algorithm.

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“…A number of techniques for modeling and simulationdriven design of microwave structures have emerged over the recent years, including the methods that exploit artificial neural networks [8,[9][10][11][12], fuzzy systems [13], kriging [14], or multidimensional Cauchy approximation [15], as well as surrogate-based techniques such as space mapping (SM) [16][17][18][19][20][21][22][23]24], simulation-based tuning [25,26], and combination of both [27,28]. The last three approaches offer computationally efficient design optimization where, under certain circumstances, a satisfactory design can be obtained after a few high-fidelity (or fine) EM simulations of the structure of interest [16].…”

Section: Introductionmentioning

confidence: 99%

Response correction techniques for surrogate-based design optimization of microwave structures

Koziel

Leifsson

2011

Int J RF and Microwave Comp Aid Eng

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Simulation-based optimization has become an important design tool in microwave engineering. However, using electromagnetic (EM) solvers in the design process is a challenging task, primarily due to a high-computational cost of an accurate EM simulation. In this article, we present a review of EM-based design optimization techniques exploiting response-corrected physically based low-fidelity models. The surrogate models created through such a correction can be used to yield a reasonable approximation of the optimal design of the computationally expensive structure under consideration (high-fidelity model). Several approaches using this idea are reviewed including output space mapping, manifold mapping, adaptive response correction, and shape-preserving response prediction. A common feature of these methods is that they are easy to implement and computationally efficient. Application examples are provided.

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Modeling and design of printed antennas using neural networks

Cited by 39 publications

References 20 publications

Obstructive uropathy caused by an inguinal hernia in a kidney transplant recipient: Report of hernia cure by the shouldice technique

Obstructive uropathy caused by an inguinal hernia in a kidney transplant recipient: Report of hernia cure by the shouldice technique

An efficient algorithm for electromagnetic scattering by a set of perfect conducting cylindrical objects using the artificial neural network

Response correction techniques for surrogate-based design optimization of microwave structures

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