2002
DOI: 10.1049/el:20021089
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Triple-stacked microstrip patch antenna for multiband system

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Cited by 18 publications
(8 citation statements)
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“…Many techniques have been used to achieve multiband operation in printed antennas including the usage of several strips, stacked structures, elongated arm, and creating different current paths . However, these techniques resulted in larger dimensions having larger ground plane thus resulting in structural complexity.…”
Section: Introductionmentioning
confidence: 99%
“…Many techniques have been used to achieve multiband operation in printed antennas including the usage of several strips, stacked structures, elongated arm, and creating different current paths . However, these techniques resulted in larger dimensions having larger ground plane thus resulting in structural complexity.…”
Section: Introductionmentioning
confidence: 99%
“…The stacked antenna is a well‐known structure for increasing the gain and bandwidth of the patch antennas. The stacked patches are used in single and array formation with various shapes such as rectangular truncated or circular .…”
Section: Introductionmentioning
confidence: 99%
“…In both categories, the development of broadband and multiband microstrip antennas is possible, as reported in the literature [1][2][3][4][5]. However, the main problem in many cases is maintaining uniformity of the radiation pattern and input impedance over the operating bands.…”
Section: Introductionmentioning
confidence: 99%
“…Besides, it can be recognized that, as far as most of the applications are concerned, the reconstruction of a buried target involves the identification of only a few parameters with regard to the geometric and dielectric properties of the target. For this reason, Caorsi et al proposed the use of neural networks to perform the online inversion of electromagnetic data scattered by buried scenarios and to recover the reconstruction of the physical properties of the investigated objects on the field with respect to the measurement campaign [4,5]. In particular, attention has been focused on the use of multilayer perceptrons (MLPs) with supervised learning [6].…”
Section: Introductionmentioning
confidence: 99%
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