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Wyniki wyszukiwania dla: SURROGATE MODELING , ANTENNA DESIGN , DOMAIN CONFINEMENT , NESTED KRIGING , DEEP NEURAL NETWORKS
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Deep CNN based decision support system for detection and assessing the stage of diabetic retinopathy
PublikacjaThe diabetic retinopathy is a disease caused by long-standing diabetes. Lack of effective treatment can lead to vision impairment and even irreversible blindness. The disease can be diagnosed by examining digital color fundus photographs of retina. In this paper we propose deep learning approach to automated diabetic retinopathy screening. Deep convolutional neural networks (CNN) - the most popular kind of deep learning algorithms...
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Surrogate methods in system engineering
Kursy Online{mlang pl} Dyscyplina: Automatyka, Elektronika i Elektrotechnika Zajęcia fakultatywne dla doktorantów II roku Prowadzący: dr hab. inż. Adrian Bekasiewicz Liczba godzin: 15 h Forma zajęć: wykład {mlang} {mlang en} Discipline: control, electronic and electrical engineering Facultative course for 2nd year PhD students Academic teacher: dr hab. inż. Adrian Bekasiewicz Total hours of training: 15 teaching hours Course...
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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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Fast multi-objective optimization of antenna structures by means of data-driven surrogates and dimensionality reduction
PublikacjaDesign of contemporary antenna structures needs to account for several and often conflicting objectives. These are pertinent to both electrical and field properties of the antenna but also its geometry (e.g., footprint minimization). For practical reasons, especially to facilitate efficient optimization, single-objective formulations are most often employed, through either a priori preference articulation, objective aggregation,...
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IEEE Transactions on Neural Networks and Learning Systems
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Optical Memory and Neural Networks (Information Optics)
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Performance‐driven modeling of compact couplers in restricted domains
PublikacjaFast surrogate models can play an important role in reducing the cost of EM-driven design closure of miniaturized microwave components. Unfortunately, construction of such models is challenging due to curse of dimensionality and wide range of geometry parameters that need to be included in order to make it practically useful. In this letter, a novel approach to design-oriented modeling of compact couplers is presented. Our method...
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Deep Learning Optimization for Edge Devices: Analysis of Training Quantization Parameters
PublikacjaThis paper focuses on convolution neural network quantization problem. The quantization has a distinct stage of data conversion from floating-point into integer-point numbers. In general, the process of quantization is associated with the reduction of the matrix dimension via limited precision of the numbers. However, the training and inference stages of deep learning neural network are limited by the space of the memory and a...
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A Modeling Problem of a Continuous-Time Domain Signal and Its Discrete Counterpart
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Efficient modeling of the time-domain crosstalk phenomena in coupled microstrip lines
PublikacjaW pracy przedstawiono efektywną technikę analizy zjawiska przesłuchu w sprzężonych liniach mikropaskowych. Analiza uwzględnia hybrydową naturę prowadzonych fal i prowadzi do określenia postaci czasowych sygnałów na zaciskach struktury w zależności od parametrów układu linii sprzężonych oraz własności obciążeń. Wyniki analizy zweryfikowano poprzez porównanie z wynikami badań eksperymentalnych, uzyskując bardzo dobrą zgodność.
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Aerodynamic Shape Optimization for Delaying Dynamic Stall of Airfoils by Regression Kriging
PublikacjaThe phenomenon of dynamic stall produce adverse aerodynamic loading which can adversely affect the structural strength and life of aerodynamic systems. Aerodynamic shape optimization (ASO) provides an effective approach for delaying and mitigating dynamic stall characteristics without the addition of auxiliary system. ASO, however, requires multiple evaluations time-consuming computational fluid dynamics models. Metamodel-based...
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Neural Approximators for Variable-Order Fractional Calculus Operators (VO-FC)
PublikacjaThe paper presents research on the approximation of variable-order fractional operators by recurrent neural networks. The research focuses on two basic variable-order fractional operators, i.e., integrator and differentiator. The study includes variations of the order of each fractional operator. The recurrent neural network architecture based on GRU (Gated Recurrent Unit) cells functioned as a neural approximation for selected...
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Active Kriging-based conjugate first-order reliability method for highly efficient structural reliability analysis using resample strategy
PublikacjaEfficient structural reliability analysis method is crucial to solving reliability analysis of complex structural problems. High-computational cost and low-failure probability problems greatly limit the efficiency in structural reliability analysis problems, causing the safety and reliability of the structure to be questioned. In this work, a highly efficient structural reliability analysis method coupling active Kriging algorithm...
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Localization in wireless sensor networks using switched parasitic antennas
PublikacjaA switched parasitic monopole antenna for 2.4 GHz ISM applications is design and investigated in this paper. One of the most promising applications for such switched-beam antennas is localization in wireless sensor networks (WSN). It is demonstrated that the use of this antenna improves accuracy of localization algorithms and allows for reduction of the number of reference nodes in localization system.
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Enhancing Renal Tumor Detection: Leveraging Artificial Neural Networks in Computed Tomography Analysis
PublikacjaRenal cell carcinoma is one of the most common cancers in Europe, with a total incidence rate of 18.4 cases per 100 000 population. There is currently significant overdiagnosis (11% to 30.9%) at times of planned surgery based on radiological studies. The purpose of this study was to create an artificial neural network (ANN) solution based on computed tomography (CT) images as an additional tool to improve the differentiation of...
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Modeling of performance of an AUV stealth vehicle. Design for operation.
PublikacjaIn the paper some results of research connected with modelling of performance and risk assessment of an AUV stealth vehicle are presented. A general approach to design of the stealth AUV autonomous underwater vehicle under consideration is introduced. The basic stealth characteristics of the AUV stealth vehicle are briefly described. The method of research is introduced. The AUV stealth vehicle concept is presented including the...
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An Improved Convolutional Neural Network for Steganalysis in the Scenario of Reuse of the Stego-Key
PublikacjaThe topic of this paper is the use of deep learning techniques, more specifically convolutional neural networks, for steganalysis of digital images. The steganalysis scenario of the repeated use of the stego-key is considered. Firstly, a study of the influence of the depth and width of the convolution layers on the effectiveness of classification was conducted. Next, a study on the influence of depth and width of fully connected...
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Analytical design of stable delta-domain generalized predictive control
PublikacjaPraca dotyczy analitycznej metody projektowania układów sterowania skalarnymi (SISO) obiektami czasu ciągłego według strategii uogólnionego sterowania predykcyjnego (GPC) w oparciu o dyskretnoczasowe modele takich obiektów. Założono wykorzystanie numeryczne odpornych modeli opartych o tak zwany operator delta. Przyjmując kwadratowy funkcjonał kosztów, w którym prognozowany przebieg przyszłego wyjścia sterowanego obiektu porównywany...
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Inverse and forward surrogate models for expedited design optimization of unequal-power-split patch couplers
PublikacjaIn the paper, a procedure for precise and expedited design optimization of unequal power split patchcouplers is proposed. Our methodology aims at identifying the coupler dimensions that correspond to thecircuit operating at the requested frequency and featuring a required power split. At the same time, thedesign process is supposed to be computationally efficient. The proposed methodology involves two typesof auxiliary models (surrogates):...
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Krzysztof Cwalina dr inż.
OsobyKrzysztof Kamil Cwalina w 2013 r. uzyskał tytuł inżyniera na Wydziale Elektroniki, Telekomunikacji i Informatyki Politechniki Gdańskiej; w 2014 r. uzyskał tytuł magistra inżyniera, a w 2017 r. otrzymał stopień doktora nauk technicznych w dyscyplinie: telekomunikacja, także na WETI PG. Aktualnie pracuje na stanowisku adiunkta w Katedrze Systemów i Sieci Radiokomunikacyjnych Wydziału Elektroniki, Telekomunikacji i Informatyki Politechniki...
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Enhancing the Seismic Resistance of Columns by GFRP Confinement Using Flexible Adhesive-Experimental Study
PublikacjaIn this paper, the results of two experiments, focused on testing the effectiveness of a method of enhancing the seismic (dynamic) resistance of masonry columns with the use of flexible polymer adhesive, are shown. The first experiment was devoted to investigate the damping properties of a polymer working between two stiff layers, whereas the aim of the second one was to verify if the identified damping properties of the polymer...
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Fast EM-Driven Nature-Inspired Optimization of Antenna Input Characteristics Using Response Features and Variable-Resolution Simulation Models
PublikacjaUtilization of optimization technique is a must in the design of contemporary antenna systems. Often, global search methods are necessary, which are associated with high computational costs when conducted at the level of full-wave electromagnetic (EM) models. In this study, we introduce an innovative method for globally optimizing reflection responses of multi-band antennas. Our approach uses surrogates constructed based on response...
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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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Determination of Odour Interactions in Gaseous Mixtures Using Electronic Nose Methods with Artificial Neural Networks
PublikacjaThis paper presents application of an electronic nose prototype comprised of eight sensors, five TGS-type sensors, two electrochemical sensors and one PID-type sensor, to identify odour interaction phenomenon in two-, three-, four- and five-component odorous mixtures. Typical chemical compounds, such as toluene, acetone, triethylamine, α-pinene and n-butanol, present near municipal landfills and sewage treatment plants were subjected...
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Design of UWB coplanar antenna with reduced ground plane
PublikacjaW artykule przedstawiono projekt kompaktowej anteny szerokopasmowej złożonej z dwóch kołowych pasków koplanarnych ograniczających szczelinę o podobnym kształcie. Antena zasilona była z 50 Ω linii trójpaskowej. Przeprowadzono badania wpływu zewnętrznego paska na pasmo anteny. Zaprojektowana antena została zbadana eksperymentalnie pokazując bardzo dobre parametry: w paśmie 1.7-15.5GHz uzyskano |S11| < −10dB. Antena charakteryzowała...
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Expedited Multi-Objective Design Optimization of Miniaturized Microwave Structures Using Physics-Based Surrogates
PublikacjaIn this paper, a methodology for fast multi-objective design optimization of compact microwave circuits is presented. Our approach exploits an equivalent circuit model of the structure under consideration, corrected through implicit and frequency space mapping, then optimized by a multi-objective evolutionary algorithm. The correction/optimization of the surrogate is iterated by design space confinement and segmentation based on...
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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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Design of Cost-Efficient Optical Fronthaul for 5G/6G Networks: An Optimization Perspective
PublikacjaCurrently, 5G and the forthcoming 6G mobile communication systems are the most promising cellular generations expected to beat the growing hunger for bandwidth and enable the fully connected world presented by the Internet of Everything (IoE). The cloud radio access network (CRAN) has been proposed as a promising architecture for meeting the needs and goals of 5G/6G (5G and beyond) networks. Nevertheless, the provisioning of cost-efficient...
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Circularly Polarized Metalens Antenna Design for 5G NR Sub-6 GHz Communication Systems
Publikacja5G NR (new radio) FR1 range refers to as Sub-6GHz band (410MHz to 7125MHz and 3.4GHz to 6GHz). In this paper, the frequency range of interest is from 3.4 to 6GHz, as many cellular companies are focusing on this Sub-6GHz band. A wideband circularly polarized (CP) antenna radiator is designed with diamond shape patches, fed by a microstrip line at the bottom through a rectangular shape wide slot on a ground plane. The proposed CP...
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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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AGENT-BASED APPROACH TO THE DESIGN OF RBF NETWORKS
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The use of fast molecular descriptors and artificial neural networks approach in organochlorine compounds electron ionization mass spectra classification
PublikacjaDeveloping of theoretical tools can be very helpful for supporting new pollutant detection. Nowadays, a combination of mass spectrometry and chromatographic techniques are the most basic environmental monitoring methods. In this paper, two organochlorine compound mass spectra classification systems were proposed. The classification models were developed within the framework of artificial neural networks (ANNs) and fast 1D and...
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Rapid Surrogate-Aided Multi-Criterial Optimization of Compact Microwave Passives Employing Machine Learning and ANNs
PublikacjaThis article introduces an innovative method for achieving low-cost and reliable multi-objective optimization (MO) of microwave passive circuits. The technique capitalizes on the attributes of surrogate models, specifically artificial neural networks (ANNs), and multi-resolution electromagnetic (EM) analysis. We integrate the search process into a machine learning (ML) framework, where each iteration produces multiple infill points...
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Neural Architecture Search for Skin Lesion Classification
PublikacjaDeep neural networks have achieved great success in many domains. However, successful deployment of such systems is determined by proper manual selection of the neural architecture. This is a tedious and time-consuming process that requires expert knowledge. Different tasks need very different architectures to obtain satisfactory results. The group of methods called the neural architecture search (NAS) helps to find effective architecture...
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Use of Neural Networks in Diagnostics of Rolling-Element Bearing of the Induction Motor
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Automatic singing voice recognition employing neural networks and rough sets
PublikacjaCelem prac opisanych w referacie jest automatyczne rozpoznawanie głosów śpiewaczych. Do tego celu utworzona została baza nagrań próbek śpiewu profesjonalnego i amatorskiego. Próbki poddane zostały parametryzacji parametrami zaproponowanymi przez autorów ściśle do tego celu. Sposób wyznaczenia parametrów i ich interpretacja fizyczna przedstawione są w referacie. Parametry wprowadzane są do systemów decyzyjnych, klasyfikatorów opartych...
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Artificial Neural Networks for Prediction of Antibacterial Activity in Series of Imidazole Derivatives
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Neural Networks Based on Ultrafast Time-Delayed Effects in Exciton Polaritons
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Analysis of electrical patterns activity in artificial multi-stable neural networks
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Optimization of a three-bed adsorption chiller by genetic algorithms and neural networks
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Extended Hopfield models of neural networks for combinatorial multiobjective optimization problems
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Neural Networks in the Diagnostics Process of Low-Power Solar Plant Devices
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Musical phrase representation and recognition by means of neural networks and rough sets.
PublikacjaW artykule przedstawiono podstawowe definicje dotyczące frazy muzycznej. W eksperymentach posłużono się zapisem parametrycznym. W celu wzmocnienia procesu rozpoznawania wykorzystano kodowanie entropijne muzyki. W eksperymentach klasyfikacji oparto się o sztuczne sieci neuronowe i metodę zbiorów przybliżonych. Słowa kluczowe: fraza muzyczna, klasyfikacja, sztuczne sieci neuronowe, metoda zbiorów przybliżonych
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Processing of musical data employing rough sets and artificial neural networks
PublikacjaArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Comparison of effectiveness of musical sound separation algorithms employing neural networks.
PublikacjaNiniejszy referat przedstawia kilka algorytmów służących do separacji dźwięków instrumentów muzycznych. Zaproponowane podejście do dekompozycji miksów dźwiękowych opiera się na założeniu, że wysokość dźwięków w miksie jest znana, tzn. wejściem dla algorytmów jest przebieg zmian wysokości dźwięków składowych miksu. Proces estymacji fazy i amplitudy składowych harmonicznych wykorzystuje dopasowywanie zespolonych przebiegów harmonicznych...
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Processing of musical data employing rough sets and artificial neural networks
PublikacjaArtykuł opisuje założenia systemu automatycznej identyfikacji muzyki i dźwięków muzycznych. Dokonano przeglądu standardu MPEG-7, ze szczególnym naciskiem na parametry opisowe dźwięku. Przedyskutowano problemy analizy danych audio, związane z zastosowaniami wykorzystującymi MPEG-7. W oparciu o eksperymenty przedstawiono efektywność deskryptorów niskiego poziomu w automatycznym rozpoznawaniu dźwięków instrumentów muzycznych. Przedyskutowano...
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Estimation of musical sound separation algorithm effectiveness employing neural networks.
PublikacjaŚlepa separacja dźwięków sygnałów muzycznych zawartych w zmiksowanym materiale jest trudnym zadaniem. Jest to spowodowane tym, że dźwięki znajdujące się w relacjach harmonicznych mogą zawierać kolidujące składowe sinusoidalne (składowe harmoniczne). Ewaluacja wyników separacji jest również problematyczna, gdyż analiza błędu energetycznego często nie odzwierciedla subiektywnej jakości odseparowanych sygnałów. W tej publikacji zostały...
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The concept of application of artificial neural networks for cultivation controlof cartilages in bioreactors.
PublikacjaNowym elementem niniejszej pracy jest omówienie problemów związanych z możliwością sterowania parametrami hydrodynamicznymi hodowanej w bioreaktorze chrząstki stawowej przy wykorzystaniu sztucznych sieci neuronowych. Przedstawiona została architektura strategii sterowania hodowlą tkanki z zastosowaniem tych sieci.
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Fast Multi-Objective Antenna Optimization Using Sequential Patching and Variable-Fidelity EM Models
PublikacjaIn this work, a technique for fast multi-objective design optimization of antenna structures is presented. In our approach, the initial approximation of the Pareto set representing the best possible trade-offs between conflicting design objectives is obtained by means of sequential patching of the design space. The latter is a stencil-based search that aims at creating a path that connects the extreme Pareto-optimal designs (obtained...
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Variable-Fidelity Simulation Models and Sparse Gradient Updates for Cost-Efficient Optimization of Compact Antenna Input Characteristics
PublikacjaDesign of antennas for the Internet of Things (IoT) applications requires taking into account several performance figures, both electrical (e.g., impedance matching) and field (gain, radiation pattern), but also physical constraints, primarily concerning size limitation. Fulfillment of stringent specifications necessitates the development of topologically complex structures described by a large number of geometry parameters that...