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Search results for: ADAPTIVE ROUTINGGLOBAL ASSOCIATION FUSIONCOMPACT POSE ESTIMATION FRAMEWORK
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Compact global association based adaptive routing framework for personnel behavior understanding
PublicationPersonnel behavior understanding under complex scenarios is a challenging task for computer vision. This paper proposes a novel Compact model, which we refer to as CGARPN that incorporates with Global Association relevance and Adaptive Routing Pose estimation Network. Our framework firstly introduces CGAN backbone to facilitate the feature representation by compressing the kernel parameter space compared with typical algorithms,...
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Shape-Based Pose Estimation of Robotic Surgical Instruments
PublicationWe describe a detector of robotic instrument parts in image-guided surgery. The detector consists of a huge ensemble of scale-variant and pose-dedicated, rigid appearance templates. The templates, which are equipped with pose-related keypoints and segmentation masks, allow for explicit pose estimation and segmentation of multiple end-effectors as well as fine-grained non-maximum suppression. We train the templates by grouping examples...
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ANN for human pose estimation in low resolution depth images
PublicationThe paper presents an approach to localize human body joints in 3D coordinates based on a single low resolution depth image. First a framework to generate a database of 80k realistic depth images from a 3D body model is described. Then data preprocessing and normalization procedure, and DNN and MLP artificial neural networks architectures and training are presented. The robustness against camera distance and image noise is analysed....
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Instrument detection and pose estimation with rigid part mixtures model in video-assisted surgeries
PublicationLocalizing instrument parts in video-assisted surgeries is an attractive and open computer vision problem. A working algorithm would immediately find applications in computer-aided interventions in the operating theater. Knowing the location of tool parts could help virtually augment visual faculty of surgeons, assess skills of novice surgeons, and increase autonomy of surgical robots. A surgical tool varies in appearance due to...
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Genetic programming extension to APF-based monocular human body pose estimation
PublicationNew method of the human body pose estimation based on a single camera 2D observation is presented, aimed at smart surveillance related video analysis and action recognition. It employs 3D model of the human body, and genetic algorithm combined with annealed particle filter for searching the global optimum of model state, best matching the object's 2D observation. Additionally, new motion cost metric is employed, considering current...
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On adaptive covariance and spectrum estimation of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one has to make two important decisions. First, one should choose the so-called estimation bandwidth, inversely proportional to the effective width of the local analysis window, in the way that complies with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive...
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On adaptive selection of estimation bandwidth for analysis of locally stationary multivariate processes
PublicationWhen estimating the correlation/spectral structure of a locally stationary process, one should choose the so-called estimation bandwidth, related to the effective width of the local analysis window. The choice should comply with the degree of signal nonstationarity. Too small bandwidth may result in an excessive estimation bias, while too large bandwidth may cause excessive estimation variance. The paper presents a novel method...
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A Framework for Adaptive and Integrated Classification
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Multiresolution analysis and adaptive estimation on a sphere using stereographic wavelets
PublicationWe construct an adaptive estimator of a density function on d dimensional unit sphere Sd (d ≥ 2), using a new type of spherical frames. The frames, or as we call them, stereografic wavelets are obtained by transforming a wavelet system, namely Daubechies, using some stereographic operators. We prove that our estimator achieves an optimal rate of convergence on some Besov type class of functions by adapting to unknown smoothness....
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Non-Adaptive Speed and Position Estimation of Doubly-Fed Induction Generator in Grid-Connected Operations
PublicationThe nonadaptive speed and position estimation scheme for a doubly-fed induction generator (DFIG) is presented in this article. The observer structure is based on the extension of the mathematical model of DFIG to the introduced H vector. Based on the defined H vector, the nonadaptive position and speed estimation is proposed. The Lyapunov method is extended to the practical stability theorem to stabilize the structure. The classic...
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Dynamic fracture of brittle shells in a space-time adaptive isogeometric phase field framework
PublicationPhase field models for fracture prediction gained popularity as the formulation does not require the specification of ad-hoc criteria and no discontinuities are inserted in the body. This work focuses on dynamic crack evolution of brittle shell structures considering large deformations. The energy contributions from in-plane and out-of-plane deformations are separately split into tensile and compressive components and the resulting...
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A probabilistic-driven framework for enhanced corrosion estimation of ship structural components
PublicationThe work proposes a probabilistic-driven framework for enhanced corrosion estimation of ship structural components using Bayesian inference and limited measurement data. The new approach for modelling measurement uncertainty is proposed based on the results of previous corrosion tests that incorporate the non-uniform character of the corroded surface of structural components. The proposed framework's basic features are outlined,...
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A novel hybrid adaptive framework for support vector machine-based reliability analysis: A comparative study
PublicationThis study presents an innovative hybrid Adaptive Support Vector Machine - Monte Carlo Simulation (ASVM-MCS) framework for reliability analysis in complex engineering structures. These structures often involve highly nonlinear implicit functions, making traditional gradient-based first or second order reliability algorithms and Monte Carlo Simulation (MCS) time-consuming. The application of surrogate models has proven effective...
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On the concept of estimation memory in adaptive filtering.
PublicationArtykuł przedstawia i omawia pojęcie pamięci estymacji, pozwalające na obiektywne porównanie właściwości śledzących różnych algorytmów adaptacyjnych filtracji.
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CNN Architectures for Human Pose Estimation from a Very Low Resolution Depth Image
PublicationThe paper is dedicated to proposing and evaluating a number of convolutional neural network architectures for calculating a multiple regression on 3D coordinates of human body joints tracked in a single low resolution depth image. The main challenge was to obtain a high precision in case of a noisy and coarse scan of the body, as observed by a depth sensor from a large distance. The regression network was expected to reason about...
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A framework for accelerated optimization of antennas using design database and initial parameter set estimation
PublicationThe purpose of this paper is to exploit a database of pre-existing designs to accelerate parametric optimization of antenna structures is investigated. Design/methodology/approach The usefulness of pre-existing designs for rapid design of antennas is investigated. The proposed approach exploits the database existing antenna base designs to determine a good starting point for structure optimization and its response sensitivities....
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Non-Adaptive Rotor Speed Estimation of Induction Machine in an Adaptive Full-Order Observer
PublicationIn the sensorless control system of an induction machine, the rotor speed value is not measured but reconstructed by an observer structure. The rotor speed value can be reconstructed by the classical adaptive law with the integrator. The second approach, which is the main contribution of this paper, is the non-adaptive structure without an integrator. The proposed method of the rotor speed reconstruction is based on an algebraic...
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Deep neural networks for human pose estimation from a very low resolution depth image
PublicationThe work presented in the paper is dedicated to determining and evaluating the most efficient neural network architecture applied as a multiple regression network localizing human body joints in 3D space based on a single low resolution depth image. The main challenge was to deal with a noisy and coarse representation of the human body, as observed by a depth sensor from a large distance, and to achieve high localization precision....
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Estimation the rhythmic salience of sound with association rules and neural networks
PublicationW referacie przedstawiono eksperymenty mające na celu automatyczne wyszukiwanie wartości rytmicznych we frazie muzycznej. W tym celu wykorzystano metody data mining i sztuczne sieci neuronowe.
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On Adaptive Spectrum Estimation of Multivariate Autoregressive Locally Stationary Processes
PublicationAutoregressive modeling is a widespread parametricspectrum estimation method. It is well known that, in the caseof stationary processes with unknown order, its accuracy canbe improved by averaging models of different complexity usingsuitably chosen weights. The paper proposes an extension of thistechnique to the case of multivariate locally stationary processes.The proposed solution is based on local autoregressive...
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A simple way of increasing estimation accuracy of generalized adaptive notch filters
PublicationGeneralized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. It is shown that frequency biases, which arisein generalized adaptive notch filtering algorithms, can be significantly reduced by incorporating in the adaptive loop an appropriately chosen decision delay. The resulting performance...
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Estimation of Housing Demand with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
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Adaptive estimation of the transformer stray capacitances for DC–DC converter modelling
PublicationNew low cost and accurate estimation method of transformer stray capacitances for wide band DC–DC converter modelling and design is proposed. The Wiener filter (WF) method is applied to estimate the transformer impedance – referred to the selected transformer winding configurations. Laboratory tests are used to adapt the filter, that is to find optimal impedance which minimises mean square error between measured, noise perturbed...
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Estimation of Housing Demand with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)
PublicationIt has always been important to anticipate the demand for a product. To determine the demand for any product, the parameters such as the economic situation and the demands of the rival products are used generally. Especially in the housing sector, which is the locomotive sector for emerging countries, it is critical to anticipate housing demand and its relationship with economic variables. Because of that, economists, real estate...
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Nonadaptive estimation of the rotor speed in an adaptive full order observer of induction machine
PublicationThe article proposes a new method of reproducing the angular speed of the rotor of a cage induction machine designed for speed observers based on the adaptive method. In the proposed solution, the value of the angular speed of the rotor is not determined by the classical law of adaptation using the integrator only by an algebraic relationship. Theoretical considerations were confirmed by simulation and experimental tests.
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High performance super-twisting sliding mode control for a maritime autonomous surface ship (MASS) using ADP-Based adaptive gains and time delay estimation
PublicationThis research addresses two kinds of problems related to optimal trajectory tracking of a Maritime Autonomous Surface Ship (MASS): those caused by the time-varying external disturbances including winds, waves and ocean currents as well as those resulting from inherent dynamical uncertainties. As the paper shows, an accurate and robust optimal controller can successfully deal with both issues. An improved Optimal Adaptive Super-Twisting...
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High performance super-twisting sliding mode control for a maritime autonomous surface ship (MASS) using ADP-Based adaptive gains and time delay estimation
PublicationThis research addresses two kinds of problems related to optimal trajectory tracking of a Maritime Autonomous Surface Ship (MASS): those caused by the time-varying external disturbances including winds, waves and ocean currents as well as those resulting from inherent dynamical uncertainties. As the paper shows, an accurate and robust optimal controller can successfully deal with both issues. An improved Optimal Adaptive Super-Twisting...
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An adaptive-noise Augmented Kalman Filter approach for input-state estimation in structural dynamics
PublicationThe establishment of a Digital Twin of an operating engineered system can increase the potency of Structural Health Monitoring (SHM) tools, which are then bestowed with enhanced predictive capabilities. This is particularly relevant for wind energy infrastructures, where the definition of remaining useful life is a main driver for assessing the efficacy of these systems. In order to ensure a proper representation of the physical...
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IATUL Seminar 2019 – ważne wydarzenie wpisujące się w rozwój działań Biblioteki Politechniki Gdańskiej na polu współpracy międzynarodowej.
PublicationCelem IATUL Seminar 2019 (Organizing the Open Science Framework – Strategies and Legal Aspects) było podsumowanie aktualnego stanu otwartości w nauce w Polsce i na świecie. Problematyka podejmowana na konferencji skupiała się na przeglądzie polityki repozytoriów instytucjonalnych i usług związanych z zarządzaniem danymi badawczymi. Poruszano także zagadnienia dotyczące aspektów prawnych związanych ze zbieraniem, przechowywaniem...
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Zdzisław Kowalczuk prof. dr hab. inż.
PeopleZdzislaw Kowalczuk received his M.Sc. degree in 1978 and Ph.D. degree in 1986, both in Automatic Control from Technical University of Gdańsk (TUG), Gdańsk, Poland. In 1993 he received his D.Sc. degree (Dr Habilitus) in Automatic Control from Silesian Technical University, Gliwice, Poland, and the title of Professor from the President of Poland in 2003. Since 1978 he has been with Faculty of Electronics, Telecommunications and Informatics...
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A new look at the statistical identification of nonstationary systems
PublicationThe paper presents a new, two-stage approach to identification of linear time-varying stochastic systems, based on the concepts of preestimation and postfiltering. The proposed preestimated parameter trajectories are unbiased but have large variability. Hence, to obtain reliable estimates of system parameters, the preestimated trajectories must be further filtered (postfiltered). It is shown how one can design and optimize such...
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Generalized adaptive notch smoothers for real-valued signals and systems
PublicationSystems with quasi-periodically varying coefficients can be tracked using the algorithms known as generalized adaptive notch filters (GANFs). GANF algorithms can be considered an extension, to the system case, of classical adaptive notch filters (ANFs). We show that estimation accuracy of the existing algorithms, as well as their robustness to the choice of design parameters, can be considerably improved by means of compensating...
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Generalized adaptive notch filters with frequency debiasing for tracking of polynomial phase systems
PublicationGeneralized adaptive notch filters are used for identification/tracking of quasi-periodically varying dynamic systems and can be considered an extension, to the system case, of classical adaptive notch filters. For general patterns of frequency variation the generalized adaptive notch filtering algorithms yield biased frequency estimates. We show that when system frequencies change slowly in a smooth way, the estimation bias can...
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efficient fractional delay hilbert transform filter in the farrow structure
PublicationIn this paper the design and application of a Fractional Delay Hilbert Transform Filter (FDHTF) into an adaptive sub-sample delay estimation between two separated sinusoidal signals is considered. The FDHTF incorporates the functions of Hilbertian and variable fractional delay filtering of the incoming signal simultaneously, in one stage. In traditional approach each of these operations was performed separately. Obtained value...
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Integrated membrane bioreactors modelling: A review on new comprehensive modelling framework
PublicationIntegrated Membrane Bioreactor (MBR) models, combination of biological and physical models, have been representing powerful tools for the accomplishment of high environmental sustainability. This paper, produced by the International Water Association (IWA) Task Group on Membrane Modelling and Control, reviews the state-of-the-art, identifying gaps for future researches, and proposes a new integrated MBR modelling framework. In...
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Selected dynamic properties of adaptive proportional observer of induction motor state variables
PublicationThis paper presents problems related to the design and the stability of adaptive proportional observer which is used for estimation of magnetic flux and motor speed in sensorless control systems of induction motor. The gain matrix of the observer was chosen by genetic algorithm and alternatively by pole placement method. It has been shown that adaptive proportional observer is stable if the...
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Adaptive Expectation Maximization Smoothing (AEMS) inverse technique forindirect fish target strenght estimation. W: [CD-ROM] Full Papers. 6th ICES Symposium on Acoustics in Fisheries and Aquatic Ecology. Montpellier, 10-14 June 2002. [Montpellier: Ifremer]**2002, [6 s.] 5 rys. bibliogr. 5 poz. Zastosowanie adaptacyjnej metody EMS do pośredniej estymacji siły celu ryb.
PublicationW pracy przedstawiono modyfikację statystycznej metody EMS (ang. Expecta-tion, Maximization, Smoothing) stosowanej w zagadnienia odwrotnych, polega-jącą na iteracyjnym rozwiązaniu równania Fredholma. Pokazano jej zastosowa-nie do pośredniej estymacji siły celu ryb stosowanej dla danych pozyskanychprzez hydroakustyczne systemy jednowiązkowe wykorzystywane w przeszukiwa-niach akustycznych. Wyniki porównano z rezultatami uzyskanymi...
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Hierarchical Estimation of Human Upper Body Based on 2D Observation Utilizing Evolutionary Programming and 'Genetic Memory'
PublicationNew method of the human body pose estimation based on single camera 2D observation is presented. It employs 3D model of the human body, and genetic algorithm combined with annealed particle filter for searching the global optimum of model state, best matching the object's 2D observation. Additionally, motion cost metric is employed, considering current pose and history of the body movement, favouring the estimates with the lowest...
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New results on estimation bandwidth adaptation
PublicationThe problem of identification of a nonstationary autoregressive signal using non-causal estimation schemes is considered. Noncausal estimators can be used in applications that are not time-critical, i.e., do not require real-time processing. A new adaptive estimation bandwidth selection rule based on evaluation of pseudoprediction errors is proposed, allowing one to adjust tracking characteristics of noncausal estimators to unknown...
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New Algorithms for Adaptive Notch Smoothing
PublicationThe problem of extraction/elimination of a nonstationary complex sinusoidal signal buried in noise is considered. This problem is usually solved using adaptive notch filtering (ANF)algorithms. It is shown that accuracy of signal estimation can be increased if the results obtained from ANF are further processed using a cascade of appropriately designed filters. The resulting adaptive notch smoothing (ANS) algorithms can be employed...
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Identification of quasi-periodically varying systems with quasi-linear frequency changes
PublicationThe problem of identification of linear quasi-periodically varying systems is considered. This problem can be solved using generalized adaptive notch filtering (GANF) algorithms. It is shown that accuracy of system parameter estimation can be increased if the results obtained from GANF are further processed using a cascade of appropriately designed filters. The resulting generalized adaptive notch smoothing (GANS) algorithms can...
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Tolerance Optimization of Antenna Structures by Means of Response Feature Surrogates
PublicationFabrication 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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ADAPTIVE IDENTIFICATION OF TIME-VARYING IMPULSE RESPONSE OF UNDERWATER ACOUSTIC COMMUNICATION CHANNEL
PublicationThe transmission properties of underwater acoustic communication channel can change dynamically due to the movement of acoustic system transmitter and receiver or underwater objects reflecting transmitted signal. The time-varying impulse response measurement and estimation are necessary to match the physical layer of data transmission to instantaneous channel propagation conditions. Using the correlative measurement method, impulse...
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MAlSim - Mobile Agent Malware Simulator
PublicationOne of the problems related to the simulation of attacks against critical infrastructures is the lack of adequate tools for the simulation of malicious software (malware). Malware attacks are the most frequent in the Internet and they pose a serious threat against critical networked infrastructures. To address this issue we developed Mobile Agent Malware Simulator (MAISim). The framework uses the technology of mobile agents and...
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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublicationThe problem of identification of nonstationary stochastic processes (systems or signals) is considered and a new class of identification algorithms, combining the basis functions approach with local estimation technique, is described. Unlike the classical basis function estimation schemes, the proposed regularized local basis function estimators are not used to obtain interval approximations of the parameter trajectory, but provide...
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Pathogenesis of psoriasis in the “omic” era. Part II. Genetic, genomic and epigenetic changes in psoriasis
PublicationPsoriasis is a multifactorial disease in which genetic, environmental and epigenetic factors regulating gene expression play a key role. In the “genomic era”, genome-wide association studies together with target genotyping platforms performed in different ethnic populations have found more than 50 genetic susceptible markers associated with the risk of psoriasis which have been identified so far. Up till now, the strongest association...
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Application of artificial intelligence into/for control of flexible manufacturing cell
PublicationThe application of artificial intelligence in technological processes control is usually limited. One problem is how to respond to changes in the environment of manufacturing system. A way to overcome the above shortcoming is to use fuzzy logic for representation of the inexact information. In this paper fundamentals of artificial intelligence and fuzzy logic are introduced from a theoretical point of view. Still more the fuzzy...
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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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Z type Observer Backstepping For Induction Machines
PublicationThis paper contains a relatively new synthesis method for non-linear objects, named backstepping. This method can be used to obtain the observer structure. The paper presents the structure of the speed observer which is a new proposition of observer backstepping with additional state variables marked Z. The rotor speed can be estimated in three different ways. The first is based on the adaptive approach, the second on the nonadaptive...
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Residue-Pole Methods for Variability Analysis of S-parameters of Microwave Devices with 3D FEM and Mesh Deformation
PublicationThis paper presents a new approach for variability analysis of microwave devices with a high dimension of uncertain parameters. The proposed technique is based on modeling an approximation of system by its poles and residues using several modeling methods, including ordinary kriging, Adaptive Polynomial Chaos (APCE), and Support Vector Machine Regression (SVM). The computational cost is compared with the traditional Monte-Carlo...