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Wyniki wyszukiwania dla: ANTENNA DESIGN, EM-DRIVEN DESIGN, LEARNING BY EXAMPLES, SURROGATE MODELING, DEEP LEARNING
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High-Efficacy Global Optimization of Antenna Structures by Means of Simplex-Based Predictors
PublikacjaDesign of modern antenna systems has become highly dependent on computational tools, especially full-wave electromagnetic (EM) simulation models. EM analysis is capable of yielding accurate representation of antenna characteristics at the expense of considerable evaluation time. Consequently, execution of simulation-driven design procedures (optimization, statistical analysis, multi-criterial design) is severely hindered by the...
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Reliable Multi-Stage Optimization of Antennas for Multiple Performance Figures in Highly-Dimensional Parameter Spaces
PublikacjaDesign of modern antenna structures needs to account for multiple performance figures and geometrical constraints. Fulfillment of these calls for the development of complex topologies described by a large number of parameters. EM-driven tuning of such designs is mandatory yet immensely challenging. In this letter, a new framework for multi-stage design optimization of multi-dimensional antennas with respect to several performance...
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Performance-driven yield optimization of high-frequency structures by kriging surrogates
PublikacjaUncertainty quantification is an important aspect of engineering design, as manufacturing toler-ances may affect the characteristics of the structure. Therefore, quantification of these effects is in-dispensable for adequate assessment of the design quality. Toward this end, statistical analysis is performed, for reliability reasons, using full-wave electromagnetic (EM) simulations. Still, the computational expenditures associated...
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Expedited antenna optimization with numerical derivatives and gradient change tracking
PublikacjaDesign automation has been playing an increasing role in the development of novel antenna structures for various applications. One of its aspects is electromagnetic (EM)-driven design closure, typically applied upon establishing the antenna topology, and aiming at adjustment of geometry parameters to boost the performance figures as much as possible. Parametric optimization is often realized using local methods given usually reasonable...
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CAD. Integrated Architectural Design, MSc Arch (2023/24)
Kursy OnlineDetailed understanding of optimizing the design process using parametric BIM (Building Information Modeling) in the Autodesk Revit Architecture program. Practical design exercises included familiarize students with methods of integrating parametric design and exchanging data with other CAD/BIM programs, modifying parametric objects and generating automatic 2D/3D architectural documentation. The lesson plan introduces students to...
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Anita Maria Dąbrowicz-Tlałka dr
OsobyUzyskała, z wynikiem bardzo dobrym, tytuł magistra na kierunku matematyka na Wydziale Matematyki Uniwersytetu Gdańskiego. Praca magisterska pt. „Zbiory swojskie i dzikie w R3” była z dziedziny topologia geometryczna. Równolegle ukończyła na Uniwersytecie Gdańskim „Podyplomowe Studium Podstaw Informatyki”. W 2001 roku uzyskała na Politechnice Poznańskiej tytuł doktora nauk matematycznych. Praca doktorska pt. „Iteracje monotoniczne...
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Tolerance-Aware Multi-Objective Optimization of Antennas by Means of Feature-Based Regression Surrogates
PublikacjaAssessing the immunity of antenna design to fabrication tolerances is an important consideration, especially when the manufacturing process has not been predetermined. At the same time, the antenna parameter tuning should be oriented toward improving the performance figures pertinent to both electrical (e.g., input matching) and field properties (e.g., axial ratio bandwidth) as much as possible. Identification of available trade-offs...
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Accurate Modeling of Frequency Selective Surfaces Using Fully-Connected Regression Model with Automated Architecture Determination and Parameter Selection Based on Bayesian Optimization
PublikacjaSurrogate modeling has become an important tool in the design of high-frequency structures. Although full-wave electromagnetic (EM) simulation tools provide an accurate account for the circuit characteristics and performance, they entail considerable computational expenditures. Replacing EM analysis by fast surrogates provides a way to accelerate the design procedures. Unfortunately, modeling of microwave passives is a challenging...
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Recent advances in high-frequency modeling by means of domain confinement and nested kriging
PublikacjaDevelopment of modern high-frequency components and circuits is heavily based on full-wave electromagnetic (EM) simulation tools. Some phenomena, although important from the point of view of the system performance, e.g., EM cross-coupling effects, feed radiation in antenna arrays, substrate anisotropy, cannot be adequately accounted for using simpler means such as equivalent network representations. Consequently, the involvement...
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Karolina Zielińska-Dąbkowska dr inż. arch.
OsobyKarolina M. Zielinska-Dabkowska (dr inż. arch., Dipl.-Ing. Arch.[FH]) jest adiunktem na Wydziale Architektury Politechniki Gdańskiej. W roku 2002 ukończyła studia na Wydziale Architektury i Urbanistyki Politechniki Gdańskiej a w 2004 inżynierii architektonicznej na HAWK Hochschule für angewandte Wissenschaft und Kunst Hildesheim w Niemczech. Po studiach pracowała dla kilku firm o światowej renomie w Berlinie, Londynie, Nowym Jorku...
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Novel Structure and EM-Driven Design of Small UWB Monopole Antenna
PublikacjaA novel structure of a small UWB monopole antenna is presented. In our approach, a compact size is achieved by means of a meander line for current path enlargement as well as the two parameterized slits that introduce additional degrees of freedom helping to ensure good impedance matching. The antenna design is carried out using surrogate-based optimization involving variable-fidelity EM simulations. This allows us to simultaneously...
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Design of microstrip antenna subarrays: a simulation-driven surrogate-based approach
PublikacjaA methodology for computationally efficient simulation-driven design of microstrip antenna subarrays is presented. Our approach takes into account the effect of the feed (here, a corporate network) on the subarray side-lobe level and allows adjustment of both radiation and reflection responses of the structure under design within a single automated process. This process is realized as surrogate-based optimization that produces...
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EM-Driven Multi-Objective Optimization of Antenna Structures in Multi-Dimensional Design Spaces
PublikacjaFeasible multi-objective optimization of antenna structures is presented. An initial set of Pareto optimal solutions is found using a multi-objective evolutionary algorithm (MOEA) working with a fast surrogate antenna model obtained by kriging interpolation of coarse-discretization EM simulation data. To make the surrogate construction computationally feasible in multi-dimensional design space, the space subset containing non-dominated...
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Design-Oriented Constrained Modeling of Antenna Structures
PublikacjaFast surrogate models are crucially important to reduce the cost of design process of antenna structures. Due to curse of dimensionality, standard (data-driven) modeling methods exhibit serious limitations concerning the number of independent geometry parameters that can be handled but also (and even more importantly) their parameter ranges. In this work, a design-oriented modeling framework is proposed in which the surrogate is...
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Nadzeya Sabatini dr
OsobyNadzeya Sabatini is Assistant Professor in Digital Transformation at Gdańsk University of Technology (Gdansk, Poland), its Department of Informatics in Management (Faculty of Management and Economics). Nadzeya is lecturer at USI – Università della Svizzera italiana (Lugano, Switzerland), a research fellow at the Institute of Digital Technologies for Communication of the same university, and coordinator of MSc in Digital Fashion...
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Model Correction and Optimization Framework for Expedited EM-Driven Surrogate-Assisted Design of Compact Antennas
PublikacjaDesign of compact antennas is a numerically challenging process that heavily relies on electromagnetic (EM) simulations and numerical optimization algorithms. For reliability of simulation results, EM models of small radiators often include connectors which—despite being components with fixed dimensions—significantly contribute to evaluation cost. In this letter, a response correction method for antenna models without connector,...
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Muhammad Jamshed Abbass Phd in Electrical Engineering
OsobyMuhammad Jamshed Abbass received the M.S. degree in electrical engineering from Riphah International University, Islamabad. He is currently pursuing the Ph.D. degree with the Wrocław University of Science and Technology, Wroclaw, Poland. His research interests include machine learning, voltage stability within power systems, control design, analysis, the modeling of electrical power systems, the integration of numerous decentralized...
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Efficient Surrogate Modeling and Design Optimization of Compact Integrated On-Chip Inductors Based on Multi-Fidelity EM Simulation Models
PublikacjaHigh-performance and small-size on-chip inductors play a critical role in contemporary radio-frequency integrated circuits. This work presents a reliable surrogate modeling technique combining low-fidelity EM simulation models, response surface approximations based on kriging interpolation, and space mapping technology. The reported method is useful for the development of broadband and highly accurate data-driven models of integrated...
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Machine-Learning-Powered EM-Based Framework for Efficient and Reliable Design of Low Scattering Metasurfaces
PublikacjaPopularity of metasurfaces has been continuously growing due to their attractive properties including the ability to effectively manipulate electromagnetic (EM) waves. Metasurfaces comprise optimized geometries of unit cells arranged as a periodic lattice to obtain a desired EM response. One of their emerging application areas is the stealth technology, in particular, realization of radar cross section (RCS) reduction. Despite...
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Deep Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Deep Learning Basics 2023/24
Kursy OnlineA course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.
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Improved-Efficacy EM-Driven Optimization of Antenna Structures Using Adaptive Design Specifications and Variable-Resolution Models
PublikacjaOptimization-driven parameter tuning is an essential step in the design of antenna systems. Although in many cases it is still conducted through parametric studies, rigorous numerical methods become a necessity if truly optimum designs are sought for, and the problem intricacies (number of variables, multiple goals, constraints) make the interactive approaches insufficient. The two practical considerations of electromagnetic (EM)-driven...
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Expedited EM-Driven Design of Miniaturized Microwave Hybrid Couplers Using Surrogate-Based Optimization
PublikacjaMiniaturization of microwave hybrid couplers is important for contemporary wireless communication engineering. Using standard computer-aided design methods for development of compact structures is extremely challenging due to a general lack of computationally efficient and accurate simulation models. Poor accuracy of available equivalent circuits results from neglecting parasitic cross-couplings that greatly affect the performance...
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Simulation-Driven Design of Microstrip Antenna Subarrays
PublikacjaA methodology for computationally efficient simulation-driven design of microstrip antenna subarrays is presented. Our approach takes into account the effect of the feed (e.g., a corporate network) on the subarray side lobe level and allows adjusting both radiation and reflection responses of the structure under design within a single automated process. This process is realized as surrogate-based optimization that produces designs...
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Efficient Multi-Objective Simulation-Driven Antenna Design Using Co-Kriging
PublikacjaA methodology for fast multi-objective antenna optimization is presented. Our approach is based on response surface approximation (RSA) modeling and variable-fidelity electromagnetic (EM) simulations. In the design process, a computationally cheap RSA surrogate model constructed from sampled coarse-discretization EM antenna simulations is optimized using a multi-objective evolutionary algorithm. The initially determined Pareto...
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Expedited EM-driven multi-objective antenna design in highly-dimensional parameter spaces
PublikacjaA technique for low-cost multi-objective optimization of antennas in highly-dimensional parameter spaces is presented. The optimization procedure is expedited by exploiting fast surrogate models, including coarse-discretization EM antenna simulations and response surface approximations (RSA). The latter is utilized to yield an initial set of Pareto non-dominated designs which are further refined using response correction methods....
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Small Antenna Design Using Surrogate-Based Optimization
PublikacjaIn this work, design of small antennas using efficient numerical optimization is investigated. We exploit variable-fidelity electromagnetic (EM) simulations and the adaptively adjusted design specifications (AADS) technique. Combination of these methods allows us to simultaneously adjust multiple geometry parameters of the antenna structure of interest in a computationally feasible manner, leading to substantial reduction of the...
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Fundamentals of Data-Driven Surrogate Modeling
PublikacjaThe primary topic of the book is surrogate modeling and surrogate-based design of high-frequency structures. The purpose of the first two chapters is to provide the reader with an overview of the two most important classes of modeling methods, data-driven (or approx-imation), as well as physics-based ones. These are covered in Chap-ters 1 and 2, respectively. The remaining parts of the book give an exposition of the specific aspects...
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Rapid Design of 3D Reflectarray Antennas by Inverse Surrogate Modeling and Regularization
PublikacjaReflectarrays (RAs) exhibit important advantages over conventional antenna arrays, especially in terms of realizing pencil-beam patterns without the employment of the feeding networks. Unfortunately, microstrip RA implementations feature narrow bandwidths, and are severely affected by losses. A considerably improved performance can be achieved for RAs involving grounded dielectric layers, which are also easy to manufacture using...
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A structure and simulation-driven design of compact CPW-fed UWB antenna
PublikacjaIn this letter, a structure of a miniaturized ultra-wideband CPW-fed antenna and its design proce-dure are presented. The antenna is a modified version of the design previously proposed in the literature, with additional degrees of freedom introduced in order to improve the structure flexibility. The small size is achieved by executing a rigorous optimization procedure that consists of two stages: (i) smart random search carried...
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Simulation-driven design of compact ultra-wideband antenna structures
PublikacjaPurpose–The purpose of this paper is to investigate strategies and algorithms for expedited designoptimization and explicit size reduction of compact ultra-wideband (UWB) antennas.Design/methodology/approach–Formulation of the compact antenna design problem aiming atexplicit size reduction while maintaining acceptable electrical performance is presented. Algorithmicframeworks are described suitable for handling various design situations...
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Fast Multi-Objective Antenna Design Through Variable-Fidelity EM Simulations
PublikacjaA technique for fast multi-objective antenna optimization is introduced. A kriging interpolation surrogate constructed from sampled coarse-mesh EM simulations is utilized by multi-objective evolutionary algorithm (MOEA) to obtain the initial Pareto front approximation. The surrogate is defined in a subset of the original design space, determined by means of independently optimized individual objectives. Response correction techniques...
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On geometry parameterization for simulation-driven design closure of antenna structures
PublikacjaFull-wave electromagnetic (EM) simulation tools have become ubiquitous in antenna design, especially final tuning of geometry parameters. From the reliability standpoint, the recommended realization of EM-driven design is through rigorous numerical optimization. It is a challenging endeavor with the major issues related to the high computational cost of the process, but also the necessity of handling several objectives and constraints...
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Editorial for the special issue on advances in forward and inverse surrogate modeling for high-frequency design
PublikacjaThe design of modern‐day high‐frequency devices and circuits, including microwave/RF, antenna and photonic components, historically has relied on full‐wave electromagnetic (EM) simulation tools. Initially used for design verification, EM simulations are nowadays used in the design process itself, for example, for finding optimum values of geometry and/or material parameters of the structures of interest. In a growing number of...
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Structure and computationally-efficient simulation-driven design of compact UWB monopole antenna
PublikacjaIn this letter, a structure of a small ultra-wideband (UWB) monopole antenna, its design optimization procedure as well as experimental validation are presented. According to our approach, antenna compactness is achieved by means of a meander line for current path enlargement as well as the two parameterized slits providing additional degrees of freedom that help to ensure good impedance matching. For the sake of reliability, the...
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On Nature-Inspired Design Optimization of Antenna Structures Using Variable-Resolution EM Models
PublikacjaNumerical optimization has been ubiquitous in antenna design for over a decade or so. It is indispensable in handling of multiple geometry/material parameters, performance goals, and constraints. It is also challenging as it incurs significant CPU expenses, especially when the underlying computational model involves full-wave electromagnetic (EM) analysis. In most practical cases, the latter is imperative to ensure evaluation reliability....
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Analysis of circular polarization antenna design trade‐offs using low‐cost EM‐driven multiobjective optimization
PublikacjaCircular polarization (CP) antennas are vital components of modern communication systems. Their design involves handling several requirements such as low reflection and axial ratio (AR) within the frequency range of interest. Small size is an important criterion for antenna mobility which is normally achieved as a by‐product of performance‐oriented modifications of the structure topology. In this work, multiobjective optimization...
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Deep Learning: A Case Study for Image Recognition Using Transfer Learning
PublikacjaDeep learning (DL) is a rising star of machine learning (ML) and artificial intelligence (AI) domains. Until 2006, many researchers had attempted to build deep neural networks (DNN), but most of them failed. In 2006, it was proven that deep neural networks are one of the most crucial inventions for the 21st century. Nowadays, DNN are being used as a key technology for many different domains: self-driven vehicles, smart cities,...
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Design-Oriented Two-Stage Surrogate Modeling of Miniaturized Microstrip Circuits with Dimensionality Reduction
PublikacjaContemporary microwave design heavily relies on full-wave electromagnetic (EM) simulation tools. This is especially the case for miniaturized devices where EM cross-coupling effects cannot be adequately accounted for using equivalent network models. Unfortunately, EM analysis incurs considerable computational expenses, which becomes a bottleneck whenever multiple evaluations are required. Common simulation-based design tasks include...
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Machine Learning Techniques in Concrete Mix Design
PublikacjaConcrete mix design is a complex and multistage process in which we try to find the best composition of ingredients to create good performing concrete. In contemporary literature, as well as in state-of-the-art corporate practice, there are some methods of concrete mix design, from which the most popular are methods derived from The Three Equation Method. One of the most important features of concrete is compressive strength, which...
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Accurate simulation-driven modeling and design optimization of compact microwave structures
PublikacjaCost efficient design optimization of microwave structures requires availability of fast yet reliable replacement models so that multiple evaluations of the structure at hand can be executed in reasonable timeframe. Direct utilization of full-wave electromagnetic (EM) simulations is often prohibitive. On the other hand, accurate data-driven modeling normally requires a very large number of training points and it is virtually infeasible...
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Multi-fidelity EM simulations and constrained surrogate modelling for low-cost multi-objective design optimisation of antennas
PublikacjaIn this study, a technique for low-cost multi-objective design optimisation of antenna structures has been proposed. The proposed approach is an enhancement of a recently reported surrogate-assisted technique exploiting variable-fidelity electromagnetic (EM) simulations and auxiliary kriging interpolation surrogate, the latter utilised to produce the initial approximation of the Pareto set. A bottleneck of the procedure for higher-dimensional...
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Neural networks and deep learning
PublikacjaIn this chapter we will provide the general and fundamental background related to Neural Networks and Deep Learning techniques. Specifically, we divide the fundamentals of deep learning in three parts, the first one introduces Deep Feed Forward Networks and the main training algorithms in the context of optimization. The second part covers Convolutional Neural Networks (CNN) and discusses their main advantages and shortcomings...
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Nested Space Mapping Technology for Expedite EM-driven Design of Compact RF/microwave Components
PublikacjaA robust simulation-driven methodology for rapid and reliable design of RF/microwave circuits comprising compact microstrip resonant cells (CMRCs) is presented. We introduce a nested space mapping (NSM) technology, in which the inner space mapping layer is utilized to improve the generalization capabilities of the equivalent circuit model corresponding to a constitutive element of the circuit under consideration. The outer layer...
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Learning design of a blended course in technical writing
PublikacjaBlending face-to-face classes with e-learning components can lead to a very successful outcome if the blend of approaches, methods, content, space, time, media and activities is carefully structured and approached from both the student’s and the tutor’s perspective. In order to blend synchronous and asynchronous e-learning activities with traditional ones, educators should make them inter-dependent and develop them according to...
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Fast surrogate-assisted simulation-driven design of compact microwave hybrid couplers
PublikacjaThis work presents a robust methodology for expedited simulation-driven design optimization of compact microwave hybrid couplers. The technique relies on problem decomposition, and a bot-tom–up design strategy, starting from the level of basic building blocks of the coupler, and finishing with a tuning procedure that exploits a fast surrogate model of the entire structure. The latter is constructed by cascading local response surface...
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Implicit Space Mapping for Variable-Fidelity EM-Driven Design of Compact Circuits
PublikacjaSpace mapping (SM) belongs to the most successful surrogate-based optimization (SBO) methods in microwave engineering. Among available SM variations, implicit SM (ISM) is particularly attractive due to its simplicity and separation of extractable surrogate model parameters and design variables of the circuit/system at hand. Unlike other SM approaches, ISM exploits a set of preassigned parameters to align the surrogate with the...
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Wiktoria Wojnicz dr hab. inż.
OsobyDSc in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2019 PhD in Mechanics (in the field of Biomechanics) - Lodz Univeristy of Technology, 2009 (with distinction) Publikacje z listy MNiSW (2009 - ) Wojnicz W., Wittbrodt E., Analysis of muscles' behaviour. Part I. The computational model of muscle. Acta of Bioengineering and Biomechanics, Vol. 11, No.4, 2009, p. 15-21 Wojnicz W., Wittbrodt E., Analysis...
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Response features for fast EM-driven design of miniaturized impedance matching transformers
PublikacjaA framework for low-cost EM-driven design optimization of compact impedance matching transformers is presented. Our technique is based on a bottom-up design where design requirements for the transformer circuit are translated into specifications for its building blocks. These elementary cells are optimized using response features. Subsequently, the entire circuit is fine-tuned using local response surface approximation models and...
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Novel structure and EM-driven design of miniaturized microstrip rat-race coupler
PublikacjaIn this paper, a novel structure and design procedure of a miniaturized microstrip rat-race coupler (RRC) is described. Small size of the RRC is achieved by folding the transmission lines of the conventional circuit into its interior, as well as by implementation of the structure on three layers. The final size of the coupler realized for the operating frequency of 1 GHz is only 220 mm2, which gives over 95% footprint reduction...