Search results for: SURROGATE-MODEL-ASSISTED EVOLUTIONARY ALGORITHM
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ESCASA : Analytical estimation of atomic coordinates from coarse‐grained geometry for nuclear‐magnetic‐resonance ‐assisted protein structure modeling. I. Backbone and Hβ protons
PublicationA method for the estimation of coordinates of atoms in proteins from coarse-grained geometry by simple analytical formulas (ESCASA), for use in nuclear-magnetic-resonance (NMR) data-assisted coarse-grained simulations of proteins is proposed. In this paper, the formulas for the backbone Hα and amide (HN) protons, and the side-chain Hβ protons, given the Cα-trace, have been derived and parameterized, by using the interproton distances...
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Image Segmentation of MRI image for Brain Tumor Detection
Publicationthis research work presents a new technique for brain tumor detection by the combination of Watershed algorithm with Fuzzy K-means and Fuzzy C-means (KIFCM) clustering. The MATLAB based proposed simulation model is used to improve the computational simplicity, noise sensitivities, and accuracy rate of segmentation, detection and extraction from MR...
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Improved maximum power point tracking algorithms by using numerical analysis techniques for photovoltaic systems
PublicationSolar photovoltaic (PV) panels generate optimal electricity when operating at the maximum power point (MPP). This study introduces a novel MPP tracking algorithm that leverages the numerical prowess of the predictor-corrector method, tailored to accommodate voltage and current fluctuations in PV panels resulting from variable environmental factors like solar irradiation and temperature. This paper delves into the intricate dynamics...
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Constrained aerodynamic shape optimization using neural networks and sequential sampling
PublicationAerodynamic shape optimization (ASO) involves computational fluid dynamics (CFD)-based search for an optimal aerodynamic shape such as airfoils and wings. Gradient-based optimization (GBO) with adjoints can be used efficiently to solve ASO problems with many design variables, but problems with many constraints can still be challenging. The recently created efficient global optimization algorithm with neural network (NN)-based prediction...
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On low-fidelity models for variable-fidelity simulation-driven design optimization of compact wideband antennas
PublicationThe paper addresses simulation-driven design optimization of compact antennas involving variable-fidelity electromagnetic (EM) simulation models. Comprehensive investigations are carried out concerning selection of the coarse model discretization density. The effects of the low-fidelity model setup on the reliability and computational complexity of the optimization process are determined using a benchmark set of three ultra-wideband...
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Modeling the Structure, Dynamics, and Transformations of Proteins with the UNRES Force Field
PublicationThe physics-based united-residue (UNRES) model of proteins ( www.unres.pl ) has been designed to carry out large-scale simulations of protein folding. The force field has been derived and parameterized based on the principles of statistical-mechanics, which makes it independent of structural databases and applicable to treat nonstandard situations such as, proteins that contain D-amino-acid residues. Powered by Langevin dynamics...
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Ligand-Modified Boron-Doped Diamond Surface: DFT Insights into the Electronic Properties of Biofunctionalization
PublicationWith the increasing power of computation systems, theoretical calculations provide a means for quick determination of material properties, laying out a research plan, and lowering material development costs. One of the most common is Density Functional Theory (DFT), which allows us to simulate the structure of chemical molecules or crystals and their interaction. In developing a new generation of biosensors, understanding the nature...
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ANALIZA MOŻLIWOŚCI ZASTOSOWANIA STEROWANIA PREDYKCYJNEGO TURBINĄ PAROWĄ ELEKTROWNI JĄDROWEJ
PublicationArtykuł przedstawia wyniki wstępnej analizy możliwości zastosowania sterowania predykcyjnego MPC turbiną parową elektrowni jądrowej. Tradycyjnie przyjmuje się, że turbina pracuje w jednym punkcie pracy odpowiadającym jej mocy nominalnej, co pozwala na stosowanie klasycznych regulatorów PID. Synteza sterowania dla warunków zmiennego punktu pracy wymaga uwzględnienia nieliniowego charakteru procesów turbiny oraz możliwości naruszania...
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Adjusted SpikeProp algorithm for recurrent spiking neural networks with LIF neurons
PublicationA problem related to the development of a supervised learning method for recurrent spiking neural networks is addressed in the paper. The widely used Leaky-Integrate-and-Fire model has been adopted as a spike neuron model. The proposed method is based on a known SpikeProp algorithm. In detail, the developed method enables gradient descent learning of recurrent or multi-layer feedforward spiking neural networks. The research included...
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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
PublicationSurrogate 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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Further Developments of the Online Sound Restoration System for Digital Library Applications
PublicationNew signal processing algorithms were introduced to the online service for audio restoration available at the web address: www.youarchive.net. Missing or distorted audio samples are estimated using a specific implementation of the Jannsen interpolation method. The algorithm is based on the autoregressive model (AR) combined with the iterative complementation of signal samples. Since the interpolation algorithm is computationally...
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Predicting emotion from color present in images and video excerpts by machine learning
PublicationThis work aims at predicting emotion based on the colors present in images and video excerpts using a machine-learning approach. The purpose of this paper is threefold: (a) to develop a machine-learning algorithm that classifies emotions based on the color present in an image, (b) to select the best-performing algorithm from the first phase and apply it to film excerpt emotion analysis based on colors, (c) to design an online survey...
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Photovoltaic Maximum Power Point Technique based on Incremental Conductance (INCON) control algorithm
PublicationMaximum output power status can significantly improve the deployment rate of solar energy system. In order to get the maximum power output, issue of tracking maximum power point (MPP), reduced harmonics around MPP and improve efficiency of the solar power energy system, this paper presents the improved maximum power point tracking (MPPT) control...
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Interference aware bluetooth scatternet (re)configuration algorithm IBLUERA
PublicationThis paper presents a new algorithm IBLUEREA, which enables reconfiguration of Bluetooth scatternet to reduce interference. IBLUEREA makes use of the complex model comparing ISM environment efficiency. The mechanism envisages the use of the assessment of the probability of successful (unsuccessful) frame transmission in order to take a decision concerning co-existence of technologies which make use of the same ISM band (here Bluetooth...
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A Novel Speed Observer for Doubly-Fed Induction Generator
PublicationThe purpose of this paper is to show a new state observer for doubly-fed generator. A proposed z-type observer algorithm based on mathematical model of doubly fed generator with additional variables treated as a disturbances has been used. A nonlinear multiscalar control method has been used to control active and reactive power of the generator. All analyses were verified by simulations and experiments tests.
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Triangulation-based Constrained Surrogate Modeling of Antennas
PublicationDesign 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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Elimination of impulsive disturbances from stereo audio recordings
PublicationThis paper presents a new approach to elimination of impulsive disturbances from stereo audio recordings. The proposed solution is based on vector autoregressive modeling of audio signals. On-line tracking of signal model parameters is performed using the stability-preserving Whittle-Wiggins-Robinson algorithm with exponential data weighting. Detection of noise pulses and model-based interpolation of the irrevocably distorted samples...
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Simplified probabilistic analysis of settlement of cyclically loaded soil stratum using point estimate method
PublicationThe paper deals with the probabilistic analysis of settlement of a non-cohesive soil layer subjected to cyclic loading. Originally, the settlement assessment is based on deterministic compaction model which requires integration of a set of differential equations. However, making use of the Bessel functions the settlement of the soil stratum can be calculated by means of simplified algorithm. The compaction model parameters were...
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Improving agility and discipline of software development with the Scrum and CMMI
PublicationThis study presents a method of combining the Scrum methodology with the CMMI maturity model to improve bothagility and discipline of software development. First, the authors propose the CMMI-Scrum reference model, which maps Scrumpractices onto 123 practices of CMMI staged levels 2 and 3. For 60% of CMMI practices, which are insufficiently covered byScrum they add new practices that improve discipline while maintaining agility....
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Modelling of Mechanical Behaviour of High-Frequency Piezoelectric Actuators Using Bouc-Wen Model
PublicationThe paper presents the application of a modified, symmetrical Bouc-Wen model to simulate a mechanical behaviour of high-frequency piezoelectric actuators (PAs). In order to identify parameters of the model, a two-step algorithm was utilized. In the first stage, the mechanical parameters were identified by taking into account their bilinear variability and using a square input voltage waveform. In the second step, the hysteresis...
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Statistically efficient smoothing algorithm for time-varying frequency estimation
PublicationThe problem of extraction/elimination of a nonstationary sinusoidal signal from noisy measurements is considered. This problem is usually solved using adaptive notch filtering (ANF) algorithms. It is shown that the accuracy of frequency estimates can be significantly increased if the results obtained from ANF are backward-time filtered by an appropriately designed lowpass filter. The resulting adaptive notch smoothing (ANS) algorithm...
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Optimized Computational Intelligence Model for Estimating the Flexural Behavior of Composite Shear Walls
PublicationThis article presents a novel approach to estimate the flexural capacity of reinforced concrete-filled composite plate shear walls using an optimized computational intelligence model. The proposed model was developed and validated based on 47 laboratory data points and the Transit Search (TS) optimization algorithm. Using 80% of the experimental dataset, the optimized model was selected by determining the unknown coefficients of...
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Impact of Low Switching-to-Fundamental Frequency Ratio on Predictive Current Control of PMSM: A simulation study
PublicationPredictive current control algorithms for permanent magnet synchronous (PMSM) drives rely on an assumption that within short intervals motor currents can be approximated with linear functions. This approximation may result either from discretizing the motor model or from simplifications applied to the continuous-time model. As the linear current approximation has been recognized as inaccurate in case when the drive operates with...
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Control System Design for Dynamic Positioning using Vectorial Backstepping
PublicationThe problem of synthesis a dynamic positioning system for low frequency model of surface vessel was considered in this paper. The recursive vectorial backstepping control design was used to keep a fixed position and heading in presence of wave disturbances. The passive observer was introduced to smooth the measurements and to estimate the velocities needed for the control algorithm. The computer simulation results were given to...
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Improved Efficacy Behavioral Modeling of Microwave Circuits through Dimensionality Reduction and Fast Global Sensitivity Analysis
PublicationBehavioral models have garnered significant interest in the realm of high-frequency electronics. Their primary function is to substitute costly computational tools, notably electromagnetic (EM) analysis, for repetitive evaluations of the structure under consideration. These evaluations are often necessary for tasks like parameter tuning, statistical analysis, or multi-criterial design. However, constructing reliable surrogate models...
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Designing of Track Axis Alignment with the Use of Satellite Measurements and Particle Swarm Optimization
PublicationDesigning of the track’s alignment is a key issue from the point of view of maintaining of proper geometries. The paper presents a design method for sections of railway line located in the horizontal arch. The method is adapted to the technique of mobile satellite measurements. The general principles of this measurement method have been described in the article. A project's solution has been presented using mathematical notation...
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Expedited Trust-Region-Based Design Closure of Antennas by Variable-Resolution EM Simulations
PublicationThe observed growth in the complexity of modern antenna topologies fostered a widespread employment of numerical optimization methods as the primary tools for final adjustment of the system parameters. This is mainly caused by insufficiency of traditional design closure approaches, largely based on parameter sweeping. Reliable evaluation of complex antenna structures requires full-wave electromagnetic (EM) analysis. Yet, EM-driven...
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Mixed integer nonlinear optimization of biological processes in wastewater sequencing batch reactor
PublicationWastewater treatment plays a key role for humanity. The waste entering lakes, rivers, and seas deteriorates daily quality of life. Therefore, it is very important to improve the efficiency of wastewater treatment. From a control point of view, a biological wastewater treatment plant is a complex, non-linear, multidimensional, hybrid control system. The paper presents the design of the optimizing hierarchical control system applied...
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Low-fidelity model considerations for simulation-based optimisation of miniaturised wideband antennas
PublicationHere, variable-fidelity electromagnetic (EM)-based design optimisation of miniaturised antennas is discussed. The authors focus on an appropriate selection of discretisation density of the low-fidelity EM model, which results in good performance of the optimisation algorithm in terms of its computational complexity and reliability. Trust-region gradient search with low-fidelity model corrected by means of non-linear frequency scaling...
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An algorithm for enhancing macromodeling in finite element analysis of waveguide components
PublicationAn algorithm for enhancing the finite element method with local model order reduction is presented. The proposed technique can be used in fast frequency domain simulation of waveguide components and resonators. The local reduction process applied to cylindrical subregions is preceded by compression of the number of variables on its boundary. As a result,the finite element large system is converted into a very compact set of linear...
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Surrogate Modeling and Optimization Using Shape-Preserving Response Prediction: A Review
PublicationComputer simulation models are ubiquitous in modern engineering design. In many cases, they are the only way to evaluate a given design with sufficient fidelity. Unfortunately, an added computa-tional expense is associated with higher fidelity models. Moreover, the systems being considered are often highly nonlinear and may feature a large number of designable parameters. Therefore, it may be impractical to solve the design problem...
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Rapid multi-objective antenna design using point-by-point Pareto set identification and local surrogate models
PublicationAntenna design is inherently a multicriterial problem.Determination of the best possible tradeoffs between conflicting objectives (a so-called Pareto front), such as reflection response, gain, and antenna size, is indispensable from the designer’s point of view, yet challenging when high-fidelity electromagnetic (EM) simulations are utilized for performance evaluation. Here, a novel and computationally...
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Variable-fidelity response feature surrogates for accelerated statistical analysis and yield estimation of compact microwave components
PublicationAccounting for manufacturing tolerances is an essential part of a reliable microwave design process. Yet, quantification of geometry and/or material parameter uncertainties is challenging at the level of full-wave electromagnetic (EM) simulation models. This is due to inherently high cost of EM analysis and massive simulations necessary to conduct the statistical analysis. Here, a low-cost and accurate yield estimation procedure...
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Trust-Based Model for the Assessment of the Uncertainty of Measurements in Hybrid IoT Networks
PublicationThe aim of this paper is to introduce a NUT model (NUT: network-uncertainty-trust) that aids the decrease of the uncertainty of measurements in autonomous hybrid Internet of Things sensor networks. The problem of uncertainty in such networks is a consequence of various operating conditions and varied quality of measurement nodes, making statistical approach less successful. This paper presents a model for decreasing the uncertainty...
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Multiobjective Water Distribution Systems Control of Pumping Cost, Water Quality, and Storage-Reliability Constraints
PublicationThis work describes a multiobjective model for trading-off pumping cost and water quality for water distribution systems operation. Constraints are imposed on flows and pressures, on periodical tanks operation, and on tanks storage. The methodology links the multiobjective SPEA2 algorithm with EPANET, and is applied on two example applications of increasing complexity, under extended period simulation conditions and variable energy...
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Visual Traffic Noise Monitoring in Urban Areas
PublicationThe paper presents an advanced system for railway and road traffic noise monitoring in metropolitan areas. This system is a functional part of a more complex solution designed for environmental monitoring in cities utilizing analyses of sound, vision and air pollution, based on a ubiquitous computing approach. The system consists of many autonomous, universal measuring units and a multimedia server, which gathers, processes and...
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Optimization of Energetic Train Cooperation
PublicationIn the article, possible ways of using energy recovered during regenerative braking of trains are presented. It is pointed out that the return of recovered electricity directly to the catenary and its use in the energy cooperation of vehicles can be a no-cost method (without additional infrastructure). The method of energy cooperation between trains and its main assumptions, that uses the law of conservation of energy, are described...
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Optimized Deep Learning Model for Flood Detection Using Satellite Images
PublicationThe increasing amount of rain produces a number of issues in Kerala, particularly in urban regions where the drainage system is frequently unable to handle a significant amount of water in such a short duration. Meanwhile, standard flood detection results are inaccurate for complex phenomena and cannot handle enormous quantities of data. In order to overcome those drawbacks and enhance the outcomes of conventional flood detection...
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Assessment of the factors influencing on the formation of energy-oriented modes of electric power consumption by water-drainage installations of the mines
PublicationPurpose. Performing the analysis to determine energy-efficient modes and assess the characteristics of the main indicators of electric power consumption by mine water-drainage installations based on the developed research mathematical model. Methods. To achieve the purpose set, a methodology is used to develop the multiple multifactor correlation-regression modeling with respect to the modes of electric power consumption by electrical...
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Consequences of New Approach of Chemical Stability Tests of Active Pharmaceutical Ingredients (APIs)
PublicationThere is a great need of broaden look on stability tests of active pharmaceuticalingredients (APIs) in comparison with current requirements contained in pharmacopeia.By usage of many modern analytical methods the conception of monitoring the changesof APIs during initial stage of their exposure to harmful factors has been developed. Newknowledge must be acquired in terms of identification of each degradation...
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Analysis of circular polarization antenna design trade‐offs using low‐cost EM‐driven multiobjective optimization
PublicationCircular 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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Supply current signal and artificial neural networks in the induction motor bearings diagnostics
PublicationThis paper contains research results of the diagnostics of induction motor bearings based on measurement of the supply current with usage of artificial neural networks. Bearing failure amount is greater than 40% of all engine failures, which makes their damage-free operation crucial. Tests were performed on motors with intentionally made bearings defects. Chapter 2 introduces the concept of artificial neural networks. It presents...
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Towards an efficient multi-stage Riemann solver for nuclear physics simulations
PublicationRelativistic numerical hydrodynamics is an important tool in high energy nuclear science. However, such simulations are extremely demanding in terms of computing power. This paper focuses on improving the speed of solving the Riemann problem with the MUSTA-FORCE algorithm by employing the CUDA parallel programming model. We also propose a new approach to 3D finite difference algorithms, which employ a GPU that uses surface memory....
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Communication Model Order Reduction in Hybrid Methods Involving Generalized Impedance Matrix
PublicationA novel strategy for the efficient analysis of frequency-domain scattering electromagnetic problems in open and closed domains is presented. A fully automatic model-order reduction technique, called the enhanced reduced-basis method, is applied to increase the efficiency of the hybrid approach, which combines the finite-element and mode-matching methods. Numerical tests show that the proposed algorithm yields reliable and highly...
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Application of mesh deformation for modeling of conformal RF components with 3D FEM
PublicationIn this paper, a method of analysis of conformal RF components has been proposed. In this approach, modeling of a curved structure is based on mesh deformation of planar objects rather than the construction of conformal geometry at CSG level. Since the model is represented as a 3D mesh, the deformation only requires the calculation of nodes position in the bent structure. The results of the proposed algorithm have been validated...
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Automatic Discovery of IaaS Cloud Workload Types
PublicationThe paper presents an approach to automatic discovery of workloads types. We perform functional characteristics of the workloads executed in our cloud environment, that have been used to create model of the computations. To categorize the resources utilization we used K-means algorithm, that allow us automatically select six types of computations. We perform analysis of the discovered types against to typical computational benchmarks,...
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Matrix Strengthening the Identification of Observations with Split Functional Models in the Squared Msplit(q) Estimation Process
PublicationThis article addresses the issue of raising the level of identification of observations with either single or more split functional models in the squared Msplit(q) estimation process. The theoretical part of the study presents the theoretical grounds for the classical method for estimating parameters in a split functional model and proposes a modification of the computational algorithm to increase the quality of the determinations...
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High-Efficacy Global Optimization of Antenna Structures by Means of Simplex-Based Predictors
PublicationDesign 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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Recent advances in high-frequency modeling by means of domain confinement and nested kriging
PublicationDevelopment 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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Design centering of compact microwave components using response features and trust regions
PublicationFabrication tolerances, as well as uncertainties of other kinds, e.g., concerning material parameters or operating conditions, are detrimental to the performance of microwave circuits. Mitigating their impact requires accounting for possible parameter deviations already at the design stage. This involves optimization of appropriately defined statistical figures of merit such as yield. Alt-hough important, robust (or tolerance-aware)...