Wyszukiwarka
dr hab. inż. Anna Pietrenko-Dąbrowska
Zatrudnienie
- Zastępca kier. katedry w Katedra Systemów Mikroelektronicznych
- Profesor uczelni w Katedra Systemów Mikroelektronicznych
Publikacje
Filtry
wszystkich: 166
Katalog Publikacji
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Obrazowanie perfuzji mózgu z wykorzystaniem modelowania parametrycznego danych DSC-MRI
PublikacjaPomiary DSC-MRI (Dynamic Susceptibility Contrast Magnetic Resonance Imaging) zostały wykorzystane w pracy do estymacji parametrów perfuzji mózgu: przepływu krwi mózgowej (cerebral blood flow, CBF), objętości krwi mózgowej (cerebral blood volume, CBV) oraz średniego czasu przejścia (mean transit time, MTT). Zaproponowano model trzykompartmentowy. Przedstawiono i porównano dwa podejścia do identyfikacji modelu na podstawie danych...
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Optymalizacja pobudzeń dla celów identyfikacji parametrów modeli zmiennych stanu
PublikacjaW pracy omówiono zagadnienie optymalizacji pobudzeń dla celów identy-fikacji parametrów modeli kompartmentowych systemów farmakokine-tycznych opisanych w kategoriach zmiennych stanu. Przedstawiono pobu-dzenia optymalne zaprojektowane według kryterium A-optymalności. Zaprojektowane pobudzenia optymalne, w obrębie klasy pobudzeń o ograniczonej energii, zapewniają maksymalną osiągalną dokładność estymat parametrów. W farmakokinetyce...
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Optymalizacja eksperymentu identyfikującego modele procesów biomedycznych
Publikacjaksiążka przedstawia wybrane metody modelowania procesów w systemach biomedycznych oraz metody optymalnej identyfikacji modeli. w rozdziale 2 zaprezentowano metodykę modelowania kinetyki substancji. omówiono kompartmentowe modelowanie struktury wewnętrznej systemu oparte na koncepcji zmiennych stanu. w rozdziale 3 przedstawiono zagadnienie optymalizacji eksperymentu biomedycznego ze szczególnym uwzględnieniem optymalizacji sygnału...
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Efficiency of new method of removing noisy background from the sequence of MRI scans depending on structure elements used to morphological processing
PublikacjaPrzedstawiono nową metodę usuwania zaszumionego tła z sekwencji skanów MRI. Każdy skan zawiera przekrój mózgu i tło, oba zaszumione. Tło należy wykluczyć z dalszej analizy. Eliminacji tła dokonano dzięki zastosowaniu opisanego algorytmu wykorzystującego podstawowe operacje morfologiczne: dylację, erozję, otwarcie i zamknięcie do uprzednio zbinaryzowanych zbiorów MRI. Zaprezentowano wyniki przetwarzania otrzymane dla różnych kształtów...
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Wpływ wyboru elementu strukturalnego użytego w przetwarzaniu morfologicznym na skuteczność nowej metody usuwania tła z sekwencji MRI
PublikacjaZaprezentowano nową metodę usuwania zaszumionego tła z sekwencji skanów MRI. Na każdy skan składają się dwa obszary: przekrój mózgu i tło, oba zawierające szum. Tło powinno być odseparowane i wykluczone z dalszej analizy. Cel ten został osiągnięty dzięki zastosowaniu opisanego algorytmu, aplikującego podstawowe operacje morfologiczne: dylację, erozję, otwarcie i zamknięcie do uprzednio zbinaryzowanych zbiorów MRI. Pokazano rezultaty...
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Optimal inputs in pharmacokinetics model's identification
PublikacjaW pracy przedstawiono zagadnienie optymalizacji pobudzeń dla identyfikacji parametrycznej kompartmentowych modeli zmiennych stanu SISO systemów farmakokinetycznych. Zaimplementowano kryterium w postaci śladu macierzy informacyjnej Fishera (kryterium czułościowe). Rozważono klasę pobudzeń dopuszczalnych o ograniczonej energii, gdyż w przypadku wielu leków zbyt szybkie ich podawanie wiąże się z występowaniem skutków ubocznych. Zadanie...
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Optymalizacja sygnału testującego dla potrzeb identyfikacji modeli procesów biologicznych i medycznych
PublikacjaRozprawa poświęcona jest optymalizacji sygnału testującego dla celów identyfikacji modeli procesów biologicznych i medycznych. Zagadnienie to zawiera się w szerszym zagadnieniu optymalizacji eksperymentu, polegającym na poszukiwaniu tej wartości wybranej zmiennej eksperymentu (w rozprawie jest to sygnał testujący), która zapewni maksimum obranego kryterium optymalności. Optymalizacja eksperymentu jest szczególnie istotna w zastosowaniach...
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Wydobywanie informacji diagnostycznej w obrazowaniu mózgu techniką MRI przy wykorzystaniu identyfikacji parametrycznej
PublikacjaDane MRI wykorzystano w pracy do oceny perfuzji tkanek mózgowych. Obrazowanie perfuzji z wykorzystaniem pomiarów MRI jest szeroko stosowane w praktyce klinicznej do diagnozowania guzów, demencji, choroby Alzheimera i innych. W modelowania danych MRI wykorzystano parametryczny model trzykompartmentowy. Parametry modelu estymowane są na podstawie danych eksperymentalnych: sygnału mierzonego w tętnicy mózgowej oraz sygnału mierzonego...
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Identyfikacja nieparametryczna systemów farmakokinetycznych metodą funkcji korelacji.
PublikacjaW pracy omówiono metodę funkcji korelacji, przedstawiono jej ograniczenia numeryczne oraz pobudzenia zapewniające maksymalną dokładność estymat odpowiedzi impulsowej w tej metodzie: szum biały oraz pobudzenia PRBS.
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Identyfikacja stałych przepływu modeli systemów farmakokinetycznych opisanych równaniami stanu. VII Ogólnopolska Konferencja Przepływów Wielofazowych.
PublikacjaPrzedstawiono identyfikację parametrów (stałych przepływu) modeli systemów farmakokinetycznych opisanych równaniami stanu.Estymowane wartości parametrów zapewniają najlepsze dopasowanie odpowiedzi modelu do danych pomiarowych. Estymację przeprowadzono metodą największej wiarygodności na podstawie pobudzenia optymalnego według kryterium optymalizacji czułościowej oraz pobudzenia impulsowego.
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Identyfikacja parametryczna modeli systemów farmakokinetycznych na podstawie pobudzenia optymalnego według kryterium optymalizacji czułościowej
PublikacjaPrzedstawiono identyfikację parametryczną modeli systemów farmakokinetycznych opisanych w kategoriach zmiennych stanu. Identyfikacja przeprowadzana jest na podstawie pobudzenia optymalnego według kryterium optymalizacji czułościowej, na które nałożono dodatkowe ograniczenia na energie i czas trwania.
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Optymalizacja pobudzeń dla celów identyfikacji parametrów kompartmentowych modeli systemów farmakokinetycznych.
PublikacjaPobudzenia optymalne, według kryterium optymalizacji czułociowej, wykorzystano do estymacji parametrów kompartmentowych modeli systemów farmakokinetycznych metodš minimalizacji błędów predykcji. Na pobudzenia optymalne nałożono ograniczenia na energię i czas trwania. Uzyskane, dla pobudzeń optymalnych, dokładnoci estymat parametrów porównano z dokładnociami uzyskanymi dla pobudzeń nieoptymalnych, standardowo stosowanych w praktyce...
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Różne kształty pobudzeń optymalnych dla celów identyfikacji parametrów modeli systemów farmakokinetycznych
PublikacjaW pracy przedstawiono optymalizację pobudzeń dla celów identyfikacji parametrycznej kompartmentowych modeli systemów farmakokinetycznych opisanych w kategorii zmiennych stanu. Stosowana w pracy funkcja kryterialna to ślad macierzy Fishera (optymalizacja czułościowa). Rozważono klasę pobudzeń optymalnych o ograniczonej energii, ze względu na występowanie w przypadku wielu leków skutków ubocznych zależnych od szybkości podania leku....
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Parametric versus nonparametric modelling of dynamic susceptibility contrast enhanced MRI based data
PublikacjaDynamic tracking of a bolus of a paramagnetic agent (dynamic susceptibility contract - DSC) in MRI (magnetic resonance imaging) measurements is successfully used for assessment of the tissue perfusion and the other features and functions of the brain (i.e. cerebral blood flow - CBF, cerebral blood volume - CBV, mean transit time - MTT). The parametric and nonparametric approaches to the identification of MRI models are presented...
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Optimal input design using sensitivity criterion for parametric identification of pharmacokinetic models
PublikacjaPrzedstawiono identyfikację parametryczną kompartmentowych modeli SISO zmiennych stanu systemów farmakokinetycznych. Struktura modelu formułowana jest na podstawie wiedzy a priori. Początkowe estymaty parametrów obliczane są w oparciu o pomiary zgromadzone w eksperymencie intuicyjnym. Na ich podstawie projektowane jest pobudzenie optymalne, które zapewnia najlepszą dokładność estymat parametrów. Przedstawiono optymalizację czułościową...
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A Novel Trust-Region-Based Algorithm with Flexible Jacobian Updates for Expedited Optimization of High-Frequency Structures
PublikacjaSimulation-driven design closure is mandatory in the design of contemporary high-frequency components. It aims at improving the selected performance figures through adjustment of the structure’s geometry (and/or material) parameters. The computational cost of this process when employing numerical optimization is often prohibitively high, which is a strong motivation for the development of more efficient methods. This is especially...
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Exploring the Beam Squint Effects on Reflectarray Perfromance: A Comprehensive Analysis of the Specular and Scattered Reflection of the Unit Cell
PublikacjaIn this article, the phenomena of beam deviation in reflectarray is discussed. The radiation pattern of the unit cell, which plays a vital role in shaping the beam of the reflectarray, is analyzed by considering undesired specular and scattered reflections. These unwanted reflections adversely affect the pattern of the single unit cell, thereby reducing the overall performance of the reflectarray. To conduct our investigations,...
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Field Calibration of Low-Cost Particulate Matter Sensors Using Artificial Neural Networks and Affine Response Correction
PublikacjaDue to detrimental effects of atmospheric particulate matter (PM), its accurate monitoring is of paramount importance, especially in densely populated urban areas. However, precise measurement of PM levels requires expensive and sophisticated equipment. Although low-cost alternatives are gaining popularity, their reliability is questionable, attributed to sensitivity to environmental conditions, inherent instability, and manufacturing...
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Statistical Data Pre-Processing and Time Series Incorporation for High-Efficacy Calibration of Low-Cost NO2 Sensor Using Machine Learning
PublikacjaAir pollution stands as a significant modern-day challenge impacting life quality, the environment, and the economy. It comprises various pollutants like gases, particulate matter, biological molecules, and more, stemming from sources such as vehicle emissions, industrial operations, agriculture, and natural events. Nitrogen dioxide (NO2), among these harmful gases, is notably prevalent in densely populated urban regions. Given...
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Low-Cost and Precise Automated Re-Design of Antenna Structures Using Interleaved Geometry Scaling and Gradient-Based Optimization
PublikacjaDesign of contemporary antennas is an intricate endeavor involving multiple stages, among others, tuning of geometry parameters. In particular, re-designing antennas to different operating frequencies, makes parametric optimization imperative to ensure the best achievable system performance. If the center frequency at the current design is distant from the target one, local tuning methods generally fail, whereas global algorithms...
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Response Feature Technology for High-Frequency Electronics. Optimization, Modeling, and Design Automation
PublikacjaThis book discusses response feature technology and its applications to modeling, optimization, and computer-aided design of high-frequency structures including antenna and microwave components. By exploring the specific structure of the system outputs, feature-based approaches facilitate simulation-driven design procedures, both in terms of improving their computational efficiency and reliability. These benefits are associated...
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Wideband High-Gain Low-Profile Series-Fed Antenna Integrated with Optimized Metamaterials for 5G millimeter Wave Applications
PublikacjaThis paper presents a series-fed four-dipole antenna with a broad bandwidth, high gain, and compact size for 5G millimeter wave (mm-wave) applications. The single dipole antenna provides a maximum gain of 6.2 dBi within its operational bandwidth, which ranges from 25.2 to 32.8 GHz. The proposed approach to enhance both gain and bandwidth involves a series-fed antenna design. It comprises four dipoles with varying lengths, and a...
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Reduced-Cost Microwave Modeling Using Constrained Domains and Dimensionality Reduction
PublikacjaDevelopment of modern microwave devices largely exploits full-wave electromagnetic (EM) simulations. Yet, simulation-driven design may be problematic due to the incurred CPU expenses. Addressing the high-cost issues stimulated the development of surrogate modeling methods. Among them, data-driven techniques seem to be the most widespread owing to their flexibility and accessibility. Nonetheless, applicability of approximation-based...
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Design and Optimization of a Compact Super-Wideband MIMO Antenna with High Isolation and Gain for 5G Applications
PublikacjaThis paper presents a super-wideband multiple-input multiple-output (SWB MIMO) antenna with low profile, low mutual coupling, high gain and compact size for microwave and millimeter wave (mm-wave) fifth-generation (5G) applications. A single antenna is a simple elliptical-square shape with a small physical size of 20 × 20 × 0.787 mm3. The combination of both square and elliptical shapes results in an exceptionally broad impedance...
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Model Management for Low-Computational-Budget Simulation-Based Optimization of Antenna Structures Using Nature-Inspired Algorithms
PublikacjaThe primary objective of this study is investigation of the possibilities of accelerating nature-inspired optimization of antenna structures using multi-fidelity EM simulation models. The primary methodology developed to achieve acceleration is a model management scheme which the level of EM simulation fidelity using two criteria: the convergence status of the optimization algorithm, and relative quality of the individual designs...
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Efficient Simulation-Based Global Antenna Optimization Using Characteristic Point Method and Nature-Inspired Metaheuristics
PublikacjaAntenna structures are designed nowadays to fulfil rigorous demands, including multi-band operation, where the center frequencies need to be precisely allocated at the assumed targets while improving other features, such as impedance matching. Achieving this requires simultaneous optimization of antenna geometry parameters. When considering multimodal problems or if a reasonable initial design is not at hand, one needs to rely...
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Machine-Learning-Based Global Optimization of Microwave Passives with Variable-Fidelity EM Models and Response Features
PublikacjaMaximizing microwave passive component performance demands precise parameter tuning, particularly as modern circuits grow increasingly intricate. Yet, achieving this often requires a comprehensive approach due to their complex geometries and miniaturized structures. However, the computational burden of optimizing these components via full-wave electromagnetic (EM) simulations is substantial. EM analysis remains crucial for circuit...
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On Accelerated Metaheuristic-Based Electromagnetic-Driven Design Optimization of Antenna Structures Using Response Features
PublikacjaDevelopment of present-day antenna systems is an intricate and multi-step process requiring, among others, meticulous tuning of designable (mainly geometry) parameters. Concerning the latter, the most reliable approach is rigorous numerical optimization, which tends to be re-source-intensive in terms of computing due to involving full-wave electromagnetic (EM) simu-lations. The cost-related issues are particularly pronounced whenever...
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Expedited Metaheuristic-Based Antenna Optimization Using EM Model Resolution Management
PublikacjaDesign of modern antenna systems heavily relies on numerical opti-mization methods. Their primary purpose is performance improvement by tun-ing of geometry and material parameters of the antenna under study. For relia-bility, the process has to be conducted using full-wave electromagnetic (EM) simulation models, which are associated with sizable computational expendi-tures. The problem is aggravated in the case of global optimization,...
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On Unsupervised Artificial-Intelligence-Assisted Design of Antennas for High-Performance Planar Devices
PublikacjaDesign of modern antenna structures is a challenging endeavor. It is laborious, and heavily reliant on engineering insight and experience, especially at the initial stages oriented towards the devel-opment of a suitable antenna architecture. Due to its interactive nature and hands-on procedures (mainly parametric studies) for validating suitability of particular geometric setups, typical antenna development requires many weeks...
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Cost-Efficient Two-Level Modeling of Microwave Passives Using Feature-Based Surrogates and Domain Confinement
PublikacjaA variety of surrogate modelling techniques has been utilized in high-frequency design over the last two decades. Yet, the curse of dimensionality still poses a serious challenge in setting up re-liable design-ready surrogates of modern microwave components. The difficulty of the model-ing task is only aggravated by nonlinearity of circuit responses. Consequently, constructing a practically usable surrogate model, valid across...
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Efficient uncertainty quantification using sequential sampling-based neural networks
PublikacjaUncertainty quantification (UQ) of an engineered system involves the identification of uncertainties, modeling of the uncertainties, and the forward propagation of the uncertainties through a system analysis model. In this work, a novel surrogate-based forward propagation algorithm for UQ is proposed. The proposed algorithm is a new and unique extension of the recent efficient global optimization using neural network (NN)-based...
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Low-Cost Behavioral Modeling of Antennas by Dimensionality Reduction and Domain Confinement
PublikacjaBehavioral modeling has been rising in importance in modern antenna design. It is primarily employed to diminish the computational cost of procedures involving massive full-wave electromagnetic (EM) simulations. Cheaper alternative offer surrogate models, yet, setting up data-driven surrogates is impeded by, among others, the curse of dimensionality. This article introduces a novel approach to reduced-cost surrogate modeling of...
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Reduced-Cost Design Optimization of High-Frequency Structures Using Adaptive Jacobian Updates
PublikacjaElectromagnetic (EM) analysis is the primary tool utilized in the design of high-frequency structures. In vast majority of cases, simpler models (e.g., equivalent networks or analytical ones) are either not available or lack accuracy: they can only be used to yield initial designs that need to be further tuned. Consequently, EM-driven adjustment of geometry and/or material parameters of microwave and antenna components is a necessary...
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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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Expedited Yield-Driven Design of High-Frequency Structures by Kriging Surrogates in Confined Domains
PublikacjaUncertainty quantification is an important aspect of engineering design, also pertaining to the development and performance evaluation of high-frequency structures 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 characteristics of antennas or microwave devices. For example, in the case...
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Performance-Driven Inverse/Forward Modeling of Antennas in Variable-Thickness Domains
PublikacjaDesign of contemporary antenna systems is a challenging endeavor. The difficulties are partially rooted in stringent specifications imposed on both electrical and field characteristics, demands concerning various functionalities, but also constraints imposed upon the physical size of the radiators. Furthermore, conducting the design process at the level of full-wave electromagnetic (EM) simulations, otherwise dictated by reliability,...
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Fundamentals of Physics-Based Surrogate Modeling
PublikacjaChapter 1 was focused on data-driven (or approximation-based) modeling methods. The second major class of surrogates are physics-based models outlined in this chapter. Although they are not as popular, their importance is growing because of the challenges related to construction and handling of approximation surrogates for many real-world problems. The high cost of evaluating computational models, nonlinearity of system responses,...
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Global Surrogate Modeling by Neural Network-Based Model Uncertainty
PublikacjaThis work proposes a novel adaptive global surrogate modeling algorithm which uses two neural networks, one for prediction and the other for the model uncertainty. Specifically, the algorithm proceeds in cycles and adaptively enhances the neural network-based surrogate model by selecting the next sampling points guided by an auxiliary neural network approximation of the spatial error. The proposed algorithm is tested numerically...
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Analysis of Agricultural and Engineering Systems using Simulation Decomposition
PublikacjaThis paper focuses on the analysis of agricultural and engineering processes using simulation decomposition (SD). SD is a technique that utilizes Monte Carlo simulations and distribution decomposition to visually evaluate the source and the outcome of different portions of data. Here, SD is applied to three distinct processes: a model problem, a nondestructive evaluation testing system, and an agricultural food-water energy system....
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Expedited Optimization of Passive Microwave Devices Using Gradient Search and Principal Directions
PublikacjaOver the recent years, utilization of numerical optimization techniques has become ubiquitous in the design of high-frequency systems, including microwave passive components. The primary reason is that the circuits become increasingly complex to meet ever growing performance demands concerning their electrical performance, additional functionalities, as well as miniaturization. Nonetheless, as reliable evaluation of microwave device...
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Global Design Optimization of Microwave Circuits Using Response Feature Inverse Surrogates
PublikacjaModern microwave design has become heavily reliant on full-wave electromagnetic (EM) simulation tools, which are necessary for accurate evaluation of microwave components. Consequently, it is also indispensable for their development, especially the adjustment of geometry parameters, oriented towards performance improvement. However, EM-driven optimization procedures incur considerable computational expenses, which may become impractical...
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Neural Network-Based Sequential Global Sensitivity Analysis Algorithm
PublikacjaPerforming global sensitivity analysis (GSA) can be challenging due to the combined effect of the high computational cost, but it is also essential for engineering decision making. To reduce this cost, surrogate modeling such as neural networks (NNs) are used to replace the expensive simulation model in the GSA process, which introduces the additional challenge of finding the minimum number of training data samples required to...
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Multi-Criterial Design of Antennas with Tolerance Analysis Using Response-Feature Predictors
PublikacjaImperfect manufacturing is one of the factors affecting the performance of antenna systems. It is particularly important when design specifications are strict and leave a minimum leeway for a degradation caused by geometry or material parameter deviations from their nominal values. At the same time, conventional antenna design procedures routinely neglect to take the fabrication tolerances into account, which is mainly a result...
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Fast Antenna Optimization Using Gradient Monitoring and Variable-Fidelity EM Models
PublikacjaAccelerated simulation-driven design optimization of antenna structures is proposed. Variable-fidelity electromagnetic (EM) analysis is used as well as the trust-region framework with limited sensitivity updates. The latter are controlled by monitoring the changes of the antenna response gradients. Our methodology is verified using three compact wideband antennas. Comprehensive benchmarking demonstrates its superiority over both...
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Low-Cost Surrogate Modeling of Miniaturized Microwave Components Using Nested Kriging
PublikacjaIn the paper, a recently reported nested kriging methodology is employed for modeling of miniaturized microwave components. The approach is based on identifying the parameter space region that contains high-quality designs, and, subsequently, rendering the surrogate in this subset. The results obtained for a miniaturized unequal-power-split rat-race coupler and a compact three-section impedance transformer demonstrate reliability...
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Reduced-Cost Constrained Modeling of Microwave and Antenna Components: Recent Advances
PublikacjaElectromagnetic (EM) simulation models are ubiquitous in the design of microwave and antenna components. EM analysis is reliable but CPU intensive. In particular, multiple simulations entailed by parametric optimization or uncertainty quantification may considerably slow down the design processes. In order to address this problem, it is possible to employ fast metamodels. Here, the popular solution approaches are approximation...
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Improved Design Closure of Compact Microwave Circuits by Means of Performance Requirement Adaptation
PublikacjaNumerical optimization procedures have been widely used in the design of microwave components and systems. Most often, optimization algorithms are applied at the later stages of the design process to tune the geometry and/or material parameter values. To ensure sufficient accuracy, parameter adjustment is realized at the level of full-wave electromagnetic (EM) analysis, which creates perhaps the most important bottleneck due to...
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On Fast Multi-objective Optimization of Antenna Structures Using Pareto Front Triangulation and Inverse Surrogates
PublikacjaDesign of contemporary antenna systems is a challenging endeavor, where conceptual developments and initial parametric studies, interleaved with topology evolution, are followed by a meticulous adjustment of the structure dimensions. The latter is necessary to boost the antenna performance as much as possible, and often requires handling several and often conflicting objectives, pertinent to both electrical and field properties...
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Expedited Trust-Region-Based Design Closure of Antennas by Variable-Resolution EM Simulations
PublikacjaThe 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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