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wybranych: 2019
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Katalog
- Publikacje 2019 wyników po odfiltrowaniu
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Filtry wybranego katalogu
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Wyniki wyszukiwania dla: NEURAL NETWORKS, SURROGATE-BASED OPTIMIZATION, HYPERPARAMETER OPTIMIZATION, SEQUENTIAL SAMPLING
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Priority-enabled optimization of resource utilization in fault-tolerant optical transport networks.
PublikacjaW artykule zaproponowano nowe podejście do optymalizacji rozdziału zasobów przeżywalnych sieci rozległych, które uzależnia szybkość przywracania ciągłości połączenia od klasy usługi. Wykazano, iż proponowana metoda nie powoduje wydłużania ścieżek zabezpieczających (w przypadku usług w wymaganej wysokiej jakości obsługi) lub czyni to w sposób minimalny (dla pozostały usług). Ze względu na fakt, że zadanie znalezienia ścieżek aktywnych...
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An optimization approach to coexistence of Bluetooth and Wi-Fi networks operating in ISM environment
PublikacjaW artykule rozważono problem wzajemnych interferencji pomiedzy urządzeniami standardów IEEE 802.11b oraz Bluetooth (BT). Zaproponowano model optymalizacyjny bazujący na podejściu programowania liniowego. Uzyskano znaczącą porawę wykorzystania pasma ISM w przypadku koegzystencji sieci rozważanych standardów.
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Packet routing and frame length optimization in wireless mesh networks with multicast communications
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Resilience through multicast – An optimization model for multi-hop wireless sensor networks
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Simultaneous Optimization of Unicast and Anycast Flows and Replica Location in Survivable Optical Networks
PublikacjaDotychczasowe prace z zakresu ochrony sieci przed awariami dotyczyły przypadku transmisji unicast. W niniejszym artykule rozważamy problem ochrony transmisji anycast (jeden-do-jednego-z-wielu). Jako wariant ochrony stosujemy podejście pojedynczej ścieżki zabezpieczającej (ang. path protection), chroniącej przed awarią pojedynczego węzła.Wprowadzono nowe modele programowania całkowitoliczbowego optymalnego znajdowania tras oraz...
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A Selection of Starting Points for Iterative Position Estimation Algorithms Using Feedforward Neural Networks
PublikacjaThis article proposes the use of a feedforward neural network (FNN) to select the starting point for the first iteration in well-known iterative location estimation algorithms, with the research objective of finding the minimum size of a neural network that allows iterative position estimation algorithms to converge in an example positioning network. The selected algorithms for iterative position estimation, the structure of the...
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Rapid design optimization of antennas using variable-fidelity EM models and adjoint sensitivities
PublikacjaPurpose – Development of techniques for expedited design optimization of complex and numerically expensive electromagnetic (EM) simulation models of antenna structures validated both numerically and experimentally. The paper aims to discuss these issues. Design/methodology/approach – The optimization task is performed using a technique that combines gradient search with adjoint sensitivities, trust region framework, as well as...
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Kriging-assisted hybrid reliability design and optimization of offshore wind turbine support structure based on a portfolio allocation strategy
PublikacjaIn recent years, offshore wind power generation technology has developed rapidly around the world, making important contributions to the further development of renewable energy. When designing an Offshore Wind Turbine (OWT) system, the uncertainties in parameters and different types of constraints need to be considered to find the optimal design of these systems. Therefore, the Reliability-Based Design Optimization (RBDO) method...
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Low-cost multi-criterial design optimization of compact microwave passives using constrained surrogates and dimensionality reduction
PublikacjaDesign of contemporary microwave circuits is a challenging task. Typically, it has to take into account several performance requirements and constraints. The design objectives are often conflicting and their simultaneous improvement may not be possible; instead, compromise solutions are to be sought. Representative examples are miniaturized microwave passives where reduction of the circuit size has a detrimental effect on its electrical...
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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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Fast Design Optimization of Waveguide Filters Applying Shape Deformation Techniques
PublikacjaThis paper presents an efficient design of microwave filters by means of geometry optimization using shape deformation techniques. This design procedure allows for modelling complex 3D geometries which can be fabricated by additive manufacturing (AM). Shape deforming operations are based on radial basis function (RBF) interpolation and are integrated into an electromagnetic field simulator based on the 3D finiteelement method (FEM)....
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USING ARTIFICIAL NEURAL NETWORKS FOR PREDICTING SHIP FUEL CONSUMPTION
PublikacjaIn marine vessel operations, fuel costs are major operating costs which affect the overall profitability of the maritime transport industry. The effective enhancement of using ship fuel will increase ship operation efficiency. Since ship fuel consumption depends on different factors, such as weather, cruising condition, cargo load, and engine condition, it is difficult to assess the fuel consumption pattern for various types...
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A dual-control strategy based on electrode material and electrolyte optimization to construct an asymmetric supercapacitor with high energy density
PublikacjaMetal-organic frames (MOFs) are regarded as excellent candidates for supercapacitors that have attracted much attention because of their diversity, adjustability and porosity. However, both poor structural stability in aqueous alkaline electrolytes and the low electrical conductivity of MOF materials constrain their practical implementation in supercapacitors. In this study, bimetallic CoNi-MOF were synthesized to enhance the electrical...
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Voltage and Reactive Power Load Flow Optimization in the Power System Using Fuzzy Logic
PublikacjaThe paper presents issues related to voltage control in the power system. An original method of reactive power flow optimization is considered, which leads to improved voltages in the power system and reduced active power losses. The optimization method is based on a procedure that employs fuzzy logic and is supported by a gradient search algorithm. The method has been implemented in PLANS software and verified.
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Tolerance Optimization of Antenna Structures by Means of Response Feature Surrogates
PublikacjaFabrication tolerances and other types of uncertainties, e.g., the lack of precise knowledge of material parameters, have detrimental effects on electrical and field performance of antenna systems. In the case of input characteristics these are particularly noticeable for narrow- and multi-band antennas where deviations of geometry parameters from their nominal values lead to frequency shifts of the operating frequency bands. Improving...
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Service-based Resilience for Embedded IoT Networks
PublikacjaEmbedded IoT networks are the backbone of safety-critical systems like smart factories, autonomous vehicles, and airplanes. Therefore, resilience against failures and attacks should be a prior concern already in their design stage. In this study, we introduce a service-based network model as an MILP optimization problem for the efficient deployment of a service overlay to the embedded network by meeting QoS and resilience requirements....
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Pareto Ranking Bisection Algorithm for Expedited Multi-Objective Optimization of Antenna Structures
PublikacjaThe purpose of this letter is introduction of a novel methodology for expedited multi-objective design of antenna structures. The key component of the presented approach is fast identification of the initial representation of the Pareto front (i.e., a set of design representing the best possible trade-offs between conflicting objectives) using a Pareto-ranking bisection algorithm. The algorithm finds a discrete set of Pareto-optimal...
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Triangulation-based Constrained Surrogate Modeling of Antennas
PublikacjaDesign of contemporary antenna structures is heavily based on full-wave electromagnetic (EM) simulation tools. They provide accuracy but are CPU-intensive. Reduction of EM-driven design procedure cost can be achieved by using fast replacement models (surrogates). Unfortunately, standard modeling techniques are unable to ensure sufficient predictive power for real-world antenna structures (multiple parameters, wide parameter ranges,...
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Aerodynamic shape optimization by variable-fidelity computational fluid dynamics models: a review of recent progress
PublikacjaA brief review of some recent variable-fidelity aerodynamic shape optimization methods is presented.We discuss three techniques that—by exploiting information embedded in low-fidelity computationalfluid dynamics (CFD) models—are able to yield a satisfactory design at a low computational cost, usu-ally corresponding to a few evaluations of the original, high-fidelity CFD model to be optimized. Thespecific techniques considered here...
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Design Space Reduction for Expedited Multi-Objective Design Optimization of Antennas in Highly-Dimensional Spaces
PublikacjaA surrogate-based technique for efficient multi-objective antenna optimization is discussed. Our approach exploits response surface approximation (RSA) model constructed from low-fidelity antenna model data (here, obtained through coarse-discretization electromagnetic simulations). The RSA model enables fast determination of the best available trade-offs between conflicting design goals. The cost of RSA model construction for multi-parameter...
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On Design Optimization of Miniaturized Microscrip Dual-Band Rat-Race Coupler with Enhanced Bandwidth
PublikacjaIn the paper, a novel topology of a miniaturized wideband dual-band rat-race coupler has been presented. Small size of the circuit has been obtained by meandering transmission lines of the conventional circuit. At the same time, the number of independent geometry parameters has been increased in order to secure sufficient circuit flexibility in the context of its design optimization for dual-band operation. Optimum dimensions of...
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Parametric optimization of sandwich composite footbridge with U-shaped cross-section
PublikacjaParametric optimization of sandwich composite footbridge was presented in the paper. Composite footbridge has 14,5 m long and has U-shaped cross-section with inner dimensions 2,6 × 1,3 m. The sandwich structure in made from GFRP laminate as a faces and PET foam as a core. The aim of analysis was to minimize the mass of the new footbridge that can lead to minimize the cost of structure. After optimization was conducted, the new...
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Expedited Yield Optimization of Narrow- and Multi-Band Antennas Using Performance-Driven Surrogates
PublikacjaUncertainty quantification is an important aspect of engineering design, also pertaining to the development and performance evaluation of antenna systems. Manufacturing tolerances as well as other types of uncertainties, related to material parameters (e.g., substrate permittivity) or operating conditions (e.g., bending) may affect the antenna characteristics. In the case of narrow- or multi-band antennas, this usually leads to...
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A novel approach exploiting properties of convolutional neural networks for vessel movement anomaly detection and classification
PublikacjaThe article concerns the automation of vessel movement anomaly detection for maritime and coastal traffic safety services. Deep Learning techniques, specifically Convolutional Neural Networks (CNNs), were used to solve this problem. Three variants of the datasets, containing samples of vessel traffic routes in relation to the prohibited area in the form of a grayscale image, were generated. 1458 convolutional neural networks with...
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An Intelligent Approach to Short-Term Wind Power Prediction Using Deep Neural Networks
PublikacjaIn this paper, an intelligent approach to the Short-Term Wind Power Prediction (STWPP) problem is considered, with the use of various types of Deep Neural Networks (DNNs). The impact of the prediction time horizon length on accuracy, and the influence of temperature on prediction effectiveness have been analyzed. Three types of DNNs have been implemented and tested, including: CNN (Convolutional Neural Networks), GRU (Gated Recurrent...
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Modelling, Simulation and Optimization of the Wavemaker in a Towing Tank
PublikacjaThe paper analyses the problem of experimental identification (frequency response), modelling and optimization of the towing tank wavemaker in the Scilab/Xcos environment. The experimental identification of the objects (the towing tank wavemaker placed in the hydrodynamic laboratory of the CTO S.A. Ship Design and Research Centre (CTO)) and the implementation of the models in the simulation environment, enable to perform: 1. tuning...
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Globalized parametric optimization of microwave components by means of response features and inverse metamodels
PublikacjaSimulation-based optimization of geometry parameters is an inherent and important stage of microwave design process. To ensure reliability, the optimization process is normally carried out using full-wave electromagnetic (EM) simulation tools, which entails significant computational overhead. This becomes a serious bottleneck especially if global search is required (e.g., design of miniaturized structures, dimension scaling over...
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Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems
PublikacjaThis paper introduces approximate analytic quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO) procedures. We present a summary of extensive research into computing. In the performed comparative study we take into account the various approaches of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces; where some executive criteria,...
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Approximate Quality Criteria for Difficult Multi-Objective Optimization Problems
PublikacjaThis paper introduces approximate analytic quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO) procedures. We present a summary of extensive research into computing. In the performed comparative study we take into account the various approaches of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces; where some executive criteria,...
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Solving highly-dimensional multi-objective optimization problems by means of genetic gender
PublikacjaPaper presents a computational optimization study using a genetic gender approach for solving multi-objective optimization problems of detection observers. In this methodology the information about an individual gender of all the considered solutions is applied for the purpose of making distinction between different groups of objectives. This information is drawn out of the fitness of individuals and applied during a current parental...
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Solving highly-dimensional multi-objective optimization problems by means of genetic gender
PublikacjaPaper presents a computational optimization study using a genetic gender approach for solving multi-objective optimization problems of detection observers. In this methodology the information about an individual gender of all the considered solutions is applied for the purpose of making distinction between different groups of objectives. This information is drawn out of the fitness of individuals and applied during a current parental...
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Expedited optimization of antenna input characteristics with adaptive Broyden updates
PublikacjaSimulation-driven adjustment of geometry and/or material parameters is a necessary step in the design of contemporary antenna structures. Due to their topological complexity, other means, such as supervised parameter sweeping, does not usually lead to satisfactory results. On the other hand, rigorous numerical optimization is computationally expensive due to a high cost of underlying full-wave electromagnetic (EM) analyses, otherwise...
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Rotational Design Space Reduction for Cost-Efficient Multi-Objective Antenna Optimization
PublikacjaCost-efficient multi-objective design of antenna structures is presented. Our approach is based on design space reduction algorithm using auxiliary single-objective optimization runs and coordinate system rotation. The initial set of Pareto-optimal solutions is obtained by optimizing a response surface approximation model established in the reduced space using coarse-discretization EM simulation data. The optimization engine is...
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Inverse modeling for fast design optimization of small-size rat-race couplers incorporating compact cells
PublikacjaIn the paper, a framework for computationally-efficient design optimization of compact rat-race couplers (RRCs) is discussed. A class of hybrid RRCs with variable operating conditions is investigated, whose size reduction is obtained by replacing ordinary transmission lines with compact microstrip resonant cells (CMRCs). Our approach employs a bottom-up design strategy leading to the development of compact RRCs through rapid design...
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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
PublikacjaRecent research reveals that multi-phase motors in electric propulsion systems are highly recommended due to their improved reliability and efficiency over traditional three phase motors. This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). A six phase squirrel cage induction...
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Particle Swarm Optimization Based Optimal Design of Six-Phase Induction Motor for Electric Propulsion of Submarines
PublikacjaAbstract: Recent research reveals that multi-phase motors in electric propulsion systems are highly recommended due to their improved reliability and efficiency over traditional three phase motors. This research presented a comparison of optimal model design of a six phase squirrel cage induction motor (IM) for electric propulsion by using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO). A six phase squirrel cage induction...
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Testing Stability of Digital Filters Using Optimization Methods with Phase Analysis
PublikacjaIn this paper, novel methods for the evaluation of digital-filter stability are investigated. The methods are based on phase analysis of a complex function in the characteristic equation of a digital filter. It allows for evaluating stability when a characteristic equation is not based on a polynomial. The operation of these methods relies on sampling the unit circle on the complex plane and extracting the phase quadrant of a function...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublikacjaA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublikacjaA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Gender approach to multi-objective optimization of detection systems by pre-selection of criteria
PublikacjaA novel idea of performing evolutionary computations for solving highly-dimensional multi-objective optimization (MOO) problems is proposed. The information about individual genders is applied. This information is drawn out of the fitness of individuals and applied during the parental crossover in the evolutionary multi-objective optimization (EMO) processes. The paper introduces the principles of the genetic-gender approach (GGA)...
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Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons
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Dynamically positioned ship steering making use of backstepping method and artificial neural networks
PublikacjaThe article discusses the issue of designing a dynamic ship positioning system making use of the adaptive vectorial backstepping method and RBF type arti cial neural networks. In the article, the backstepping controller is used to determine control laws and neural network weight adaptation laws. e arti cial neural network is applied at each time instant to approximate nonlinear functions containing parametric uncertainties....
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Approximate Criteria for the Evaluation of Truly Multi-Dimensional Optimization Problems
PublikacjaIn this paper we propose new improved approximate quality criteria useful in assessing the efficiency of evolutionary multi-objective optimization (EMO). In the performed comparative study we take into account the various EMO algorithms of the state-of-the-art, in order to objectively assess the EMO performance in highly dimensional spaces. It is well known that useful executive criteria, such as those based on the true Pareto...
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Hybrid of Neural Networks and Hidden Markov Models as a modern approach to speech recognition systems
PublikacjaThe aim of this paper is to present a hybrid algorithm that combines the advantages ofartificial neural networks and hidden Markov models in speech recognition for control purpos-es. The scope of the paper includes review of currently used solutions, description and analysis of implementation of selected artificial neural network (NN) structures and hidden Markov mod-els (HMM). The main part of the paper consists of a description...
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Low-cost multi-objective optimization of antennas using Pareto front exploration and response features
PublikacjaIn the paper, a procedure for low-cost multi-objective optimization of antenna structures is presented. Our approach is based on exploration of the Pareto front representing the best possible trade-offs between conflicting objectives, here, the structure size and its electrical performance. Starting from the design representing the best in-band reflection level, subsequent Pareto-optimal designs are identified through local constrained...
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Interior Point Method Evaluation for Reactive Power Flow Optimization in the Power System
PublikacjaThe paper verifies the performance of an interior point method in reactive power flow optimization in the power system. The study was conducted on a 28 node CIGRE system, using the interior point method optimization procedures implemented in Power Factory software.
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Use of AMI Meters in the Process of Low Voltage Grid Optimization
PublikacjaThis is a report of a project involving, inter alia, low voltage grid performance optimization with data from AMI meters . The study was supported with a European UPGRID grant, and executed by a consortium of companies from seven European countries, including Poland .
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PLC-based Implementation of Stochastic Optimization Method in the Form of Evolutionary Strategies for PID, LQR, and MPC Control
PublikacjaProgrammable logic controllers (PLCs) are usually equipped with only basic direct control algorithms like proportional-integral-derivative (PID). Modules included in engineering software running on a personal computer (PC) are usually used to tune controllers. In this article, an alternative approach is considered, i.e. the development of a stochastic optimizer based on the (μ,λ) evolution strategy (ES) in a PLC. For this purpose,...
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Generalized Formulation of Response Features for Reliable Optimization of Antenna Input Characteristics
PublikacjaElectromagnetic (EM)-driven parameter adjustment has become imperative in the design of modern antennas. It is necessary because the initial designs rendered through topology evolution, parameter sweeping, or theoretical models, are often of poor quality and need to be improved to satisfy stringent performance requirements. Given multiple objectives, constraints, and a typically large number of geometry parameters, the design closure...
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Design and Optimization of a Compact Planar Radiator for UWB Applications and Beyond
PublikacjaA compact monopole antenna for ultra-wideband (UWB) and beyond applications has been proposed. The radiator is based on the monopole topology. The super-wideband behavior has been achieved using a combination of spline-based modifications applied to the driven element, as well as utilization of a tapered feed and a slot-modified ground plane. The electrical performance of the structure has been tuned using a numerical optimization...