2008
DOI: 10.1002/mop.23771
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Artificial neural network applications in improved noise wave modeling of microwave FETs

Abstract: The structure of the proposed fishbone-shaped antenna with a V-slot for dual-band operation makes it possible to easily design a high-performance dual-band antenna by adjusting the location and number of fishbones on both sides of a basic antenna with a V-slot at the center. This design can be applied to various types of microstripRecently, many different wireless communication companies have been offering services using different frequency bands, and even the same services often use different frequency bands … Show more

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Cited by 7 publications
(3 citation statements)
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“…HEMTs based on the well‐established GaAs technology are very suited for low‐noise applications at microwave frequencies. Over the years, many studies have been devoted to the characterization of GaAs HEMTs in terms of the noise ( N ‐) parameters and to their modeling . A typical approach consists of using the equivalent‐circuit representation and assigning an equivalent noise temperature to each resistor.…”
Section: Introductionmentioning
confidence: 99%
“…HEMTs based on the well‐established GaAs technology are very suited for low‐noise applications at microwave frequencies. Over the years, many studies have been devoted to the characterization of GaAs HEMTs in terms of the noise ( N ‐) parameters and to their modeling . A typical approach consists of using the equivalent‐circuit representation and assigning an equivalent noise temperature to each resistor.…”
Section: Introductionmentioning
confidence: 99%
“…The field of electrical engineering has proved to be a very suitable for the ANN applications [26][27][28][29][30][31][32][33][34][35]. By learning the dependence between two datasets, ANNs have the capability to approximate any nonlinear function, whereby the knowledge about the physical characteristics of the problem to be modeled is not needed [36].…”
Section: Noise De-embedding Procedures Using Artificial Neural Networkmentioning
confidence: 99%
“…Surrogate models can be based on different modeling approaches, such as: polynomial response surfaces; support vector machines; space mapping; kriging; ANNs (Güneş et al, 2007(Güneş et al, , 2014De Tommasi et al, 2010, 2011Yelten et al, 2012). The ANN computational approach has gained recognition as an unconventional and a very useful modeling tool in the area of microwaves (Zhang and Gupta, 2000;Rayas-Sanchez, 2004;Marinković et al, 2008Marinković et al, , 2010Marinković et al, , 2012Marinković et al, , 2013Kabir et al, 2010;Agatonović et al, 2012;Hayati and Akhlaghi, 2013). A feature of neural networks, qualifying them to be used in various modeling applications, is their ability to learn the dependence between two data sets.…”
Section: Introductionmentioning
confidence: 99%