Relevant bibliographies by topics / Microwave networks

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Microwave networks'

Author: Grafiati
Published: 7 December 2024

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Journal articles on the topic "Microwave networks"

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Son, Wonhyung, Won-Kwang Park, and Seong-Ho Son. "A Neural Network-Based Microwave Imaging Method for Object Localization." Journal of Electromagnetic Engineering and Science 22, no. 5 (September 30, 2022): 576–79. http://dx.doi.org/10.26866/jees.2022.5.r.125.

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This paper presents a new microwave imaging method using artificial neural networks to localize an object. The trained neural network reconstructs a tomographic image from the measured scattering data, such as a nonlinear electromagnetic inverse scattering solver. The appropriate number of hidden neurons is determined through the cross-entropy between network predictions and target values. To verify this method experimentally, we set up a testbed consisting of 16 antennas that transmit and receive 950 MHz microwaves underwater and used a metal rod with a diameter of 2 mm as a localizing target. The results show excellent imaging performance with fewer artifacts and less than a 2-mm localization error.
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Stepanets, I. V., V. A. Stepanets, E. M. Zaychik, and S. M. Odoevsky. "FEATURES OF THE APPLICATION AND PLANNING OF THE MICROWAVE TRANSMISSION IN THE 5th GENERATION NETWORKS." Informatization and communication, no. 3 (May 24, 2019): 77–83. http://dx.doi.org/10.34219/2078-8320-2019-10-3-77-83.

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Goal. Architecture and radio access technologies of 5G networks set high requirements towards throughput, latency and reliability of the distributive transport networks. Regarding to this, the goal of this paper is to carry out the analysis of actual characteristics of microwave transmission planning and its application, which is essential for the wireless segment of the distributive transport network of 5G. Materials and methods. The requirements for automatization of the planning processes were defined for communication networks in general and for microwave transmission in particular. This requirements definition is based on analysis of 5G network architecture, its characteristics and development tendency. The automatization must embrace all of the planning phases, including the solutions of the calculation and information tasks. Moreover, the automatization must represent an instrument for the decision support in development, modernization and optimization of the telecommunication networks, including microwave transmission. This must be based on the modelling within a specialized software platform, which is able to cooperate with the external databases and management systems. Results. The longstanding research of the authors is embodied in the software complex for planning and optimization of telecommunication networks ONEPLAN, which has a module architecture. This allows to carry out the planning and optimization of microwave transmission, throughput capabilities and data traffic distribution within the transport networks, as well as to make the analysis for data traffic reliability. Conclusion. Planning process automatization by the software platform ONEPLAN maintains efficiently the forehanded, technically and economically reasonable decision making for the development, modernization and optimization of the telecommunication networks including the wireless segment of 5G transport networks based on microwave transmission.
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Semennikov, Anton V. "MICROWAVE ELECTRONICS TECHNOLOGIES FOR 5G AND 6G WIRELESS NETWORKS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 9/6, no. 150 (2024): 176–84. http://dx.doi.org/10.36871/ek.up.p.r.2024.09.06.020.

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The article is devoted to the study of microwave electronics technologies, which play a key role in the development of fifth- and sixth-generation wireless networks (5G and 6G). The main aspects of the development and integration of microwave components, including power amplifiers, antennas, and modulators, are considered, and the challenges and prospects for their application are discussed. Particular attention is paid to innovations in the field of materials science and semiconductors, which can significantly improve network performance, providing high data rates and low latencies. Forecasts are given for the further development of microwave technologies in the context of 6G networks.
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Overeem, A., H. Leijnse, and R. Uijlenhoet. "Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network." Atmospheric Measurement Techniques Discussions 8, no. 8 (August 7, 2015): 8191–230. http://dx.doi.org/10.5194/amtd-8-8191-2015.

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Abstract. Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide rainfall maps can be derived from the signal attenuations of microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm and provide the corresponding code. Moreover, the code (in the scripting language "R") is made available including a data set of commercial microwave links. The purpose of this paper is to promote rainfall monitoring utilizing microwave links from cellular communication networks as an alternative or complementary means for global, continental-scale rainfall monitoring.
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Katkevičius, Andrius, Darius Plonis, Robertas Damaševičius, and Rytis Maskeliūnas. "Trends of Microwave Devices Design Based on Artificial Neural Networks: A Review." Electronics 11, no. 15 (July 28, 2022): 2360. http://dx.doi.org/10.3390/electronics11152360.

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The usage of techniques of the artificial neural networks (ANNs) in the field of microwave devices has recently increased. The advantages of ANNs in comparison with traditional full-wave methods are that the prediction speed when the traditional time-consuming iterative calculations are not required and also the complex mathematical model of the microwave device is no longer needed. Therefore, the design of microwave device could be repeated many times in real time. However, methods of artificial neural networks still lag behind traditional full-wave methods in terms of accuracy. The prediction accuracy depends on the structure of the selected neural network and also on the obtained dataset for the training of the network. Therefore, the paper presents a systematic review of the implementation of ANNs in the field of the design and analysis of microwave devices. The guidelines for the systematic literature review and the systematic mapping research procedure, as well as the Preferred Report Items for Systematic Reviews and Meta-Analysis statements (PRISMA) are used to conduct literature search and report the results. The goal of the paper is to summarize the application areas of usage of ANNs in the field of microwave devices, the type and structure of the used artificial neural networks, the type and size of the dataset, the interpolation and the augmentation of the training dataset, the training algorithm and training errors and also to discuss the future perspectives of the usage of ANNs in the field of microwave devices.
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Wang, Lin, Guangying Wang, and Jingxu Chen. "IOT-Based Injection-Locked Microwave Photonic Frequency Division Signal Processing." Mobile Information Systems 2022 (September 27, 2022): 1–10. http://dx.doi.org/10.1155/2022/1351399.

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When building an injection-locked microwave photonic frequency division signal processing model for the Internet of Things, the waveform and frequency of the microwave have an important impact on its performance. How to optimize and adjust the injection-locked microwave photonic frequency division signal processing effect needs more research and exploration. Taking the traditional mode architecture as a reference, this paper constructs an injection-locked microwave photonic frequency division signal processing model based on the Internet of Things. In this paper, the popular deep analysis method is used to optimize the model, and the photonic technology is matched with the microwave analysis. The purpose of this construction is to weaken the microwave integration error and improve the calculation accuracy to a higher level. In addition, aiming at the difficult problem of microwave signal generation, this paper uses the optical injection method to lock the microwave photons and generate waveform signals, which makes the model data more representative, so as to solve the problems of unstable microwave signals and high transmission costs. This paper also discusses the possibility of microwave photon filtering and frequency division signal processing of microwaves. The optimal solution is determined by analyzing the experimental results of various technical means, thus proving that the injection-locked microwave photonic frequency division signal processing means has better stability and a higher fitting degree.
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Milovanovic, Bratislav, Vera Markovic, Zlatica Marinkovic, and Zoran Stankovic. "Some applications of neural networks in microwave modeling." Journal of Automatic Control 13, no. 1 (2003): 39–46. http://dx.doi.org/10.2298/jac0301039m.

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This paper presents some applications of neural networks in the microwave modeling. The applications are related to modeling of either passive or active structures and devices. Modeling is performed using not only simple multilayer perception network (MLP) but also advanced knowledge based neural network (KBNN) structures.
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Overeem, Aart, Hidde Leijnse, and Remko Uijlenhoet. "Retrieval algorithm for rainfall mapping from microwave links in a cellular communication network." Atmospheric Measurement Techniques 9, no. 5 (June 1, 2016): 2425–44. http://dx.doi.org/10.5194/amt-9-2425-2016.

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Abstract. Microwave links in commercial cellular communication networks hold a promise for areal rainfall monitoring and could complement rainfall estimates from ground-based weather radars, rain gauges, and satellites. It has been shown that country-wide (≈ 35 500 km2) 15 min rainfall maps can be derived from the signal attenuations of approximately 2400 microwave links in such a network. Here we give a detailed description of the employed rainfall retrieval algorithm. Moreover, the documented, modular, and user-friendly code (a package in the scripting language “R”) is made available, including a 2-day data set of approximately 2600 commercial microwave links from the Netherlands. The purpose of this paper is to promote rainfall mapping utilising microwave links from cellular communication networks as an alternative or complementary means for continental-scale rainfall monitoring.
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Mu, Zhong Guo, Xue Lian Bai, Yi Ding Luo, Jian Ting Mei, and Ming Hu Zhang. "Study on Microwave Curing of Polyurethane (PU)/Epoxy (EP) Interpenetrating Networks (IPN)." Applied Mechanics and Materials 556-562 (May 2014): 649–52. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.649.

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Microwave curing of PU/EP IPN was studied in this paper. Microwave curing IPN was prepared by means of intermittent microwave heating, The results indicates that microwave curing technique can shorten curing time remarkably. The microwave curing and thermal curing IPN have identical structure, tensile property of microwave curing IPN is better than that of thermal curing IPN, Impact strength of thermal curing IPN is slightly higher.
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Wang, Lulu. "Holographic Microwave Image Classification Using a Convolutional Neural Network." Micromachines 13, no. 12 (November 23, 2022): 2049. http://dx.doi.org/10.3390/mi13122049.

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Holographic microwave imaging (HMI) has been proposed for early breast cancer diagnosis. Automatically classifying benign and malignant tumors in microwave images is challenging. Convolutional neural networks (CNN) have demonstrated excellent image classification and tumor detection performance. This study investigates the feasibility of using the CNN architecture to identify and classify HMI images. A modified AlexNet with transfer learning was investigated to automatically identify, classify, and quantify four and five different HMI breast images. Various pre-trained networks, including ResNet18, GoogLeNet, ResNet101, VGG19, ResNet50, DenseNet201, SqueezeNet, Inception v3, AlexNet, and Inception-ResNet-v2, were investigated to evaluate the proposed network. The proposed network achieved high classification accuracy using small training datasets (966 images) and fast training times.
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Dissertations / Theses on the topic "Microwave networks"

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Mohammad, Malik Adeel, and Saeed Muhammad Sheharyar. "Load Balancing in Microwave Networks." Thesis, KTH, Skolan för informations- och kommunikationsteknik (ICT), 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-121698.

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Microwave links are very commonly used in carrier networks especially towards the access side. They not only ease deployment of a network but are also very cost effective. However, they bring along a multitude of challenges which are characteristic of the wireless technology. Microwave links are fickle. Being exposed to varying weather conditions, they experience bandwidth fluctuations. This is true especially in the case of links operating at higher frequencies. The unpredictable nature of microwave links makes it quite challenging to plan capacity in a network beforehand. Radio links employ adaptive modulation. They operate on a range on modulation schemes each of which offers different throughput and bit error rates. When operating at a low bit rate modulation scheme, a situation may arise where the microwave link is not able to support the entire traffic incident from the backbone network. As a result, the microwave link will suffer from congestion and packets arriving at the microwave link will eventually be dropped. The switching nodes that precede the microwave link along a communication path are unaware of the microwave link conditions and, therefore, continue to transmit traffic at a high rate. Large carrier networks cannot afford to have performance inconsistencies like data loss and increased latency. Service degradation, even for a very short duration, can have dire consequences in terms of customer dissatisfaction and revenue loss. The goal of this thesis is to use MPLS-TP Linear Protection to load balance traffic across alternative paths in a network where links use adaptive modulation. Rerouted traffic must take other paths so that the congested microwave link is completely avoided. The idea is augmented by the use of a radio condition signaling mechanism between the packet switching node and the microwave node that precede a microwave link. The microwave node sends radio condition control messages to the preceding packet switching node to rate limit traffic and avoid congestion at the microwave link. The result of this thesis work is a system prototype that achieves the stated goal. Evaluation of the prototype is carried out through graphical results, generated by a traffic generator, that advocate the correctness, performance and robustness of the system.
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McKenzie, Wilfred. "Characterisation of microwave passive networks based on electromagnetic analysis." Thesis, University of Leeds, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.278080.

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Wang, Fang. "Knowledge based neural networks for microwave modeling and design." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp02/NQ37081.pdf.

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Dias, De Macedo Filho Antonio. "Microwave neural networks and fuzzy classifiers for ES systems." Thesis, University College London (University of London), 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.244066.

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Wang, Fang Carleton University Dissertation Engineering Electronics. "Knowledge based neural networks for microwave modeling and design." Ottawa, 1998.

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Basarudin, Hafiz. "Development of a heterogeneous microwave network, fade simulation tool applicable to networks that span Europe." Thesis, University of Hull, 2012. http://hydra.hull.ac.uk/resources/hull:5774.

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Radio communication systems operating at microwave frequencies are strongly attenuated by hydrometeors such as rain and wet snow (sleet). Hydrometeor attenuation dominates the dynamic fading of most types of radio links operating above 10 GHz, especially high capacity, fixed, terrestrial and Earth-Space links. The International Telecommunication Unions – Radio Section (ITU-R) provides a set of internationally recognized models to predict annual fade distributions for a wide variety of individual radio link. However, these models are not sufficient for the design and optimisation of networks, even as simple as two links. There are considerable potential gains to be achieved from the optimized design of real-time or predictive Dynamic Resource Management systems. The development of these systems requires a joint channel simulation tool applicable to arbitrary, heterogeneous networks. This thesis describes the development of a network fade simulation tool, known as GINSIM, which can simulate joint dynamic fade time-series on heterogeneous networks of arbitrary geometry, spanning Europe. GINSIM uses as input meteorological and topological data from a variety of sources and numerically calculates the joint effects on fading on all links in a specified network. ITU-R models are used to transform rain rate into specific attenuation and to estimate the specific attenuation amplification due to non-liquid hydrometeors. The resulting simulation tool has been verified against ITU-R models of average annual fade distributions, fade slope and fade duration distributions, in the southern UK. Validation has also been performed against measured terrestrial and Earth-space link data, acquired in the Southern UK and Scotland.
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Muñoz-Arcos, Christian Daniel. "Optical Microwave Signal Generation for Data Transmission in Optical Networks." Thesis, Toulouse, ISAE, 2020. http://www.theses.fr/2020ESAE0013.

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La croissance des services de télécommunications et l’augmentation du trafic de données àl’échelle mondiale favorise le développement et l’intégration de différents réseaux de transmissionde données. Un exemple de ce développement est constitué par les réseaux defibres optiques, qui sont actuellement chargés d’interconnecter les continents par des liaisonslongues avec des taux de transfert importants. Les réseaux optiques, ainsi que les réseauxsupportés par d’autres moyens de transmission, utilisent des signaux électriques à certainesfréquences pour la synchronisation des éléments du réseau. La qualité de ces signaux est unfacteur décisif dans la performance globale du système, c’est pourquoi leur bruit de phasedoit ˆetre aussi faible que possible.Ce document décrit la conception et la mise en œuvre d’un système optoélectronique pour lagénération de signaux micro-ondes à l’aide de diodes laser à cavité verticale (VCSEL) et sonintégration dans un système de transmission optique de données. Compte tenu du fait que lesystème proposé intègre un laser VCSEL directement modulé, une caractérisation théoriqueet expérimentale a été élaborée sur la base des équations d’évolution du laser, de mesuresdynamiques et statiques, et d’un modèle électrique équivalent de la région active. Cetteméthode a permis l’extraction de certains paramètres intrinsèques du VCSEL, ainsi que lavalidation et la simulation de ses performances dans différentes conditions de modulation.Le VCSEL utilisé émet en bande C et a été sélectionné en considérant que cette bande estcouramment utilisée dans les liaisons à longue distance.Le système proposé est constitué d’une boucle fermée qui déclenche l’oscillation grâce auxsources de bruit des composants et module le VCSEL en fort signal pour générer des impulsionsoptiques (gain switching). Ces impulsions optiques, qui dans le domaine des fréquencescorrespondent à un peigne de fréquences optiques, sont détectées pour générer simultanémentune fréquence fondamentale (déterminée par un filtre passe-bande) et plusieurs harmoniques.Le bruit de phase mesuré à10 kHz de la porteuse à1,25 GHz est de -127,8 dBc/Hz, etconstitue la valeur la plus faible signalée dans la littérature pour cette fréquence et cette architecture.La gigue et la largeur d’impulsion optique ont été déterminées lorsque différentescavités résonantes et différents courants de polarisation étaient utilisés. La durée d’impulsion
The massive growth of telecommunication services and the increasing global data traffic boostthe development, implementation, and integration of different networks for data transmission.An example of this development is the optical fiber networks, responsible today for theinter-continental connection through long-distance links and high transfer rates. The opticalnetworks, as well as the networks supported by other transmission media, use electricalsignals at specific frequencies for the synchronization of the network elements. The qualityof these signals is usually determined in terms of phase noise. Due to the major impact ofthe phase noise over the system performance, its value should be minimized.The research work presented in this document describes the design and implementation ofan optoelectronic system for the microwave signal generation using a vertical-cavity surfaceemittinglaser (VCSEL) and its integration into an optical data transmission system. Consideringthat the proposed system incorporates a directly modulated VCSEL, a theoreticaland experimental characterization was developed based on the laser rate equations, dynamicand static measurements, and an equivalent electrical model of the active region. This proceduremade possible the extraction of some VCSEL intrinsic parameters, as well as thevalidation and simulation of the VCSEL performance under specific modulation conditions.The VCSEL emits in C-band, this wavelength was selected because it is used in long-haullinks. The proposed system is a self-initiated oscillation system caused by internal noise sources,which includes a VCSEL modulated in large signal to generate optical pulses (gain switching).The optical pulses, and the optical frequency comb associated, generate in electricaldomain simultaneously a fundamental frequency (determined by a band-pass filter) and severalharmonics. The phase noise measured at 10 kHz from the carrier at 1.25 GHz was -127.8dBc/Hz, and it is the lowest value reported in the literature for this frequency and architecture.Both the jitter and optical pulse width were determined when different resonantcavities and polarization currents were employed. The lowest pulse duration was 85 ps andwas achieved when the fundamental frequency was 2.5 GHz. As for the optical frequencycomb, it was demonstrated that its flatness depends on the electrical modulation conditions.The flattest profiles are obtained when the fundamental frequency is higher than the VCSELrelaxation frequency. Both the electrical and the optical output of the system were integrated into an optical transmitter.The electrical signal provides the synchronization of the data generating equipment,whereas the optical pulses are employed as an optical carrier. Data transmissions at 155.52Mb/s, 622.08 Mb/s and 1.25 Gb/s were experimentally validated. It was demonstrated thatthe fundamental frequency and harmonics could be extracted from the optical data signaltransmitted by a band-pass filter. It was also experimentally proved that the pulsed returnto-zero (RZ) transmitter at 1.25 Gb/s, achieves bit error rates (BER) lower than 10−9 whenthe optical power at the receiver is higher than -33 dBm. la plus faible, 85 ps, a été obtenue lorsque la fréquence fondamentale du système était de 2,5 GHz. En ce qui concerne le peigne de fréquences optiques, il a été démontré que la formedu peigne dépend des conditions de modulation électrique et que les profils les plus platssont obtenus lorsque la fréquence fondamentale est supérieure à la fréquence de relaxationdu VCSEL. Les sorties électrique et optique du système ont été intégrées dans un émetteur optique. Lesignal électrique permet la synchronisation de l’équipement responsable de la génération desdonnées, tandis que les impulsions optiques sont utilisées comme porteuse optique. La transmissionde données à 155,52 Mb/s, 622,08 Mb/s et 1,25 Gb/s a été validée expérimentalement
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Hedrick, Jeffrey C. "High performance polymeric networks and thermoplastic blends : microwave versus thermal processing /." Diss., This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-07122007-103925/.

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Thesis (Ph. D.)--Virginia Polytechnic Institute and State University, 1991.
Vita. Abstract. No film copy made for this title. Includes bibliographical references (leaves 243-254). Also available via the Internet.
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Lochtie, Gail D. "Propagation at microwave frequencies in the presence of tropospheric stratified layers." Thesis, University of Essex, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.303451.

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Pratap, Rana Jitendra. "Design and Optimization of Microwave Circuits and Systems Using Artificial Intelligence Techniques." Diss., Georgia Institute of Technology, 2005. http://hdl.handle.net/1853/7225.

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In this thesis, a new approach combining neural networks and genetic algorithms is presented for microwave design. In this method, an accurate neural network model is developed from the experimental data. This neural network model is used to perform sensitivity analysis and derive response surfaces. An innovative technique is then applied in which genetic algorithms are coupled with the neural network model to assist in synthesis and optimization. The proposed method is used for modeling and analysis of circuit parameters for flip chip interconnects up to 35 GHz, as well as for design of multilayer inductors and capacitors at 1.9 GHz and 2.4 GHz. The method was also used to synthesize mm wave low pass filters in the range of 40-60 GHz. The devices obtained from layout parameters predicted by the neuro-genetic design method yielded electrical response close to the desired value (95% accuracy). The proposed method also implements a weighted priority scheme to account for tradeoffs in microwave design. This scheme was implemented to synthesize bandpass filters for 802.11a and HIPERLAN wireless LAN applications in the range of 5-6 GHz. This research also develops a novel neuro-genetic design centering methodology for yield enhancement and design for manufacturability of microwave devices and circuits. A neural network model is used to calculate yield using Monte Carlo methods. A genetic algorithm is then used for yield optimization. The proposed method has been used for yield enhancement of SiGe heterojunction bipolar transistor and mm wave voltage-controlled oscillator. It results in significant yield enhancement of the SiGe HBTs (from 25 % to 75 %) and VCOs (from 8 % to 85 %). The proposed method is can be extended for device, circuit, package, and system level integrated co-design since it can handle a large number of design variables without any assumptions about the component behavior. The proposed algorithm could be used by microwave community for design and optimization of microwave circuits and systems with greater accuracy while consuming less computational time.
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Books on the topic "Microwave networks"

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Strobel, Otto, ed. Optical and Microwave Technologies for Telecommunication Networks. Chichester, UK: John Wiley & Sons, Ltd, 2016. http://dx.doi.org/10.1002/9781119114857.

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Lehpamer, Harvey. Microwave transmission networks: Planning, design, and deployment. 2nd ed. New York: McGraw-Hill, 2010.

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Lehpamer, Harvey. Microwave transmission networks: Planning, design, and deployment. 2nd ed. New York: McGraw-Hill, 2010.

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Lehpamer, Harvey. Microwave transmission networks: Planning, design, and deployment. 2nd ed. New York: McGraw-Hill, 2010.

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Lo, Jonathan O. Y. Time domain finite element analysis of microwave planar networks. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1992.

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Feher, Kamilo. Digital communications: Microwave applications. New Delhi: Prentice-Hall, 1987.

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Wincza, Krzysztof. Design of microwave networks with broadband directional couplers: Projektowanie układów mikrofalowych wykorzystujących szerokopasmowe sprzęgacze kierunkowe. Krakow: AGH University of Science and Technology Press, 2011.

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Dobrowolski, Janusz. Computer-aided analysis, modeling, and design of microwave networks: The wave approach. Boston: Artech House, 1996.

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J, Reddy C., and Langley Research Center, eds. Application of FEM to estimate complex permittivity of dielectric material at microwave frequency using waveguide measurements. Hampton, Va: National Aeronautics and Space Administration, Langley Research Center, 1995.

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Cataldo, Andrea. Broadband Reflectometry for Enhanced Diagnostics and Monitoring Applications. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011.

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Book chapters on the topic "Microwave networks"

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Benson, F. A., and T. M. Benson. "Microwave networks." In Fields, Waves and Transmission Lines, 150–83. Dordrecht: Springer Netherlands, 1991. http://dx.doi.org/10.1007/978-94-011-2382-2_6.

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Nadiv, Ron. "Microwave Backhaul Networks." In Convergence of Mobile and Stationary Next-Generation Networks, 163–202. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2010. http://dx.doi.org/10.1002/9780470630976.ch6.

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Qin, Juehang, and A. Hubler. "Reducing Microwave Absorption with Chaotic Microwaves." In Lecture Notes in Networks and Systems, 119–26. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52621-8_11.

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Noghanian, Sima, Abas Sabouni, Travis Desell, and Ali Ashtari. "Inclusion of A Priori Information Using Neural Networks." In Microwave Tomography, 87–141. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0752-6_5.

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Martín, Ferran, Jordi Naqui, Francisco Medina, Lei Zhu, and Jiasheng Hong. "INTRODUCTION TO BALANCED TRANSMISSION LINES, CIRCUITS, AND NETWORKS." In Balanced Microwave Filters, 1–20. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2018. http://dx.doi.org/10.1002/9781119238386.ch1.

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Raghunandan, Krishnamurthy. "Microwave and Millimeter-Wave Links." In Introduction to Wireless Communications and Networks, 277–96. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92188-0_14.

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Al-Zoubi, Abdallah. "Flipping the Microwave Engineering Class." In Lecture Notes in Networks and Systems, 809–19. Cham: Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-26876-2_77.

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Koul, Shiban Kishen, and Sukomal Dey. "Micromachined Microwave Phase Shifters." In Radio Frequency Micromachined Switches, Switching Networks, and Phase Shifters, 77–100. Boca Raton, FL : CRC Press, Taylor & Francis Group, [2019]: CRC Press, 2019. http://dx.doi.org/10.1201/9781351021340-5.

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Sisodiya, Divya, Yash Bahuguna, Akanksha Srivastava, and Gurjit Kaur. "Green Microwave and Satellite Communication Systems." In Green Communication Technologies for Future Networks, 231–52. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003264477-13.

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Guglielmi, M. "Microwave Networks and the Method of Moments." In Applied Computational Electromagnetics, 131–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59629-2_8.

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Conference papers on the topic "Microwave networks"

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Masud, Md Abdullah Al, Alazar Araia, Yuxin Wang, Jianli Hu, and Yuhe Tian. "Machine Learning-Aided Process Design for Microwave-Assisted Ammonia Production." In Foundations of Computer-Aided Process Design, 316–21. Hamilton, Canada: PSE Press, 2024. http://dx.doi.org/10.69997/sct.121422.

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Abstract:
Machine learning (ML) has become a powerful tool to analyze complex relationships between multiple variables and to unravel valuable information from big datasets. However, an open research question lies in how ML can accelerate the design and optimization of processes in the early experimental development stages with limited data. In this work, we investigate the ML-aided process design of a microwave reactor for ammonia production with exceedingly little experimental data. We propose an integrated approach of synthetic minority oversampling technique (SMOTE) regression combined with neural networks to quantitatively design and optimize the microwave reactor. To address the limited data challenge, SMOTE is applied to generate synthetic data based on experimental data at different reaction conditions. Neural network has been demonstrated to effectively capture the nonlinear relationships between input features and target outputs. The softplus activation function is used for a smoother prediction compared to the Rectified Linear Unit activation function. Ammonia concentration is predicted using pressure, temperature, feed flow rate, and feed composition ratio as input variables. For point-wise prediction based on discrete operating conditions, the proposed SMOTE integrated neural network approach outperforms with 96.1% accuracy compared to neural networks (without SMOTE), support vector regression, and linear regression. The multi-variate prediction trends are also validated which are critical for design optimization.
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Gemmato, Valentina, Filippo Scotti, Federico Camponeschi, Luca Rinaldi, Marco Bartocci, Claudio Porzi, and Paolo Ghelfi. "Microwave Photonics Optical Filter for ESM Systems." In 2024 24th International Conference on Transparent Optical Networks (ICTON), 1–4. IEEE, 2024. http://dx.doi.org/10.1109/icton62926.2024.10647818.

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PIRKL, W. "MICROWAVE ELECTRONICS – MICROWAVE NETWORKS." In Proceedings of the Joint US-CERN-Japan International School. WORLD SCIENTIFIC, 1999. http://dx.doi.org/10.1142/9789814447324_0004.

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Lembo, Leonardo, Salvatore Maresca, Giovanni Serafino, Filippo Scotti, Antonio Malacarne, Paolo Ghelfi, and Antonella Bogoni. "Microwave Photonics for a Radar Network." In Photonic Networks and Devices. Washington, D.C.: OSA, 2019. http://dx.doi.org/10.1364/networks.2019.neth2d.2.

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Kodjo, Alvinice, Brigitte Jaumard, Napoleao Nepomuceno, Mejdi Kaddour, and David Coudert. "Dimensioning microwave wireless networks." In 2015 IEEE International Conference on Signal Processing for Communications (ICC). IEEE, 2015. http://dx.doi.org/10.1109/icc.2015.7248751.

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Minasian, R. A., X. Yi, and L. Li. "Microwave photonic processing of high-speed microwave signals." In 2016 18th International Conference on Transparent Optical Networks (ICTON). IEEE, 2016. http://dx.doi.org/10.1109/icton.2016.7550273.

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Zvonimir Vrazic, Dubravko Zagar, and Sonja Grgic. "Adaptive modulation in microwave networks." In ELMAR 2007. IEEE, 2007. http://dx.doi.org/10.1109/elmar.2007.4418841.

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Charalambous, Georgios, and Stavros Iezekiel. "Microwave Photonic Linear Frequency Networks." In 2019 21st International Conference on Transparent Optical Networks (ICTON). IEEE, 2019. http://dx.doi.org/10.1109/icton.2019.8840536.

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Globa, L., Y. Demidova, and M. Ternovoy. "Network Anomaly Detection using Neural Networks." In 2006 16th International Crimean Microwave and Telecommunication Technology. IEEE, 2006. http://dx.doi.org/10.1109/crmico.2006.256445.

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Carpintero, Guillermo, Muhsin Ali, Luis Enrique García-Muñoz, Frédéric van Dijk, Robinson Cruzoe Guzman, Douwe H. Geuzebroek, Chris G. H. Roeloffzen, David de Felipe, and Norbert Keil. "Advances in hybrid integrated microwave photonic systems for millimeter- and Terahertz wave generation." In Photonic Networks and Devices. Washington, D.C.: OSA, 2020. http://dx.doi.org/10.1364/networks.2020.netu3b.4.

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Reports on the topic "Microwave networks"

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Singh, D., M. J. Salter, and N. M. Ridler. Comparison of Vector Network Analyser (VNA) calibration techniques at microwave frequencies. National Physical Laboratory, September 2020. http://dx.doi.org/10.47120/npl.tqe14.

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Wong, N. C. Optical-to-Microwave Frequency Chain Utilizing a Two-Laser-Based Optical Parametric Oscillator Network,. Fort Belvoir, VA: Defense Technical Information Center, September 1995. http://dx.doi.org/10.21236/ada300860.

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Duda, L. E. User manual for CSP{_}VANA: A check standards measurement and database program for microwave network analyzers. Office of Scientific and Technical Information (OSTI), October 1997. http://dx.doi.org/10.2172/541945.

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