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Search results for: gaussian unitary ensemble
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Convex set of quantum states with positive partial transpose analysed by hit and run algorithm
PublicationThe convex set of quantum states of a composite K×K system with positive partial transpose is analysed. A version of the hit and run algorithm is used to generate a sequence of random points covering this set uniformly and an estimation for the convergence speed of the algorithm is derived. For K >3 or K=3 this algorithm works faster than sampling over the entire set of states and verifying whether the partial transpose is positive....
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Generic appearance of objective results in quantum measurements
PublicationMeasurement is of central interest in quantum mechanics as it provides the link between the quantum world and the world of everyday experience. One of the features of everyday experience is its robust, objective character, contrasting the delicate nature of quantum systems. Here we analyze in a completely model-independent way the celebrated von Neumann measurement process, using recent techniques of information flow, studied in...
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Divide and not forget: Ensemble of selectively trained experts in Continual Learning
PublicationClass-incremental learning is becoming more popular as it helps models widen their applicability while not forgetting what they already know. A trend in this area is to use a mixture-of-expert technique, where different models work together to solve the task. However, the experts are usually trained all at once using whole task data, which makes them all prone to forgetting and increasing computational burden. To address this limitation,...
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Moments of Hermite-Gaussian functionals
PublicationMoments of finite products of Hermite-Gaussian functionals are expressed by covariances of Gaussian sequence.
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Note on the variance of the sum of gaussian functonals
PublicationDowodzi się oszacowania wariancji sum funkcjonałów losowych, konstruowanych dla zależnego ciągu gaussowskiego.Let (Xi; i = 1; 2; : : :) be a Gaussian sequence with Xi 2 N(0; 1) for each i and suppose its correlation matrix R = (ij)i;j1 is the matrix of some linear operator R : l2 ! l2. Then for fi 2 L 2(), i = 1; 2; : : : ; where is the standard normal distribution, we estimate the variation of the sum of the Gaussian functionals...
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SOME CONVERGENCE PROPERTIES OF THE SUM OF GAUSSIAN FUNCTIONALS
PublicationIn the paper, some aspects of the convergence of series of dependent Gaussian sequences problem are solved. The necessary and sufficient conditions for the convergence of series of centered dependent indicators are obtained. Some strong convergence results for weighted sums of Gaussian functionals are discussed.
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Estimation of a Stochastic Burgers' Equation Using an Ensemble Kalman Filter
PublicationIn this work, we consider a difficult problem of state estimation of nonlinear stochastic partial differential equations (SPDE) based on uncertain measurements. The presented solution uses the method of lines (MoL), which allows us to discretize a stochastic partial differential equation in a spatial dimension and represent it as a system of coupled continuous-time ordinary stochastic differential equations (SDE). For such a system...
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Estimation of blood pressure parameters using ex-Gaussian model
PublicationThe paper presents an example of model-based estimation of blood pressure parameters (onset, systolic and diastolic pressure) from continuous measurements. First, the signal was low pass filtered and its quality was estimated. Good quality periods were divided into beats using an electrocardiogram. Next, the beginning of each beat of the blood pressure signal was approximated basing on the function created from the sum of two independent...
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Electrochemistry from first-principles in the grand canonical ensemble
PublicationProgress in electrochemical technologies, such as automotive batteries, supercapacitors, and fuel cells, depends greatly on developing improved charged interfaces between electrodes and electrolytes. The rational development of such interfaces can benefit from the atomistic understanding of the materials involved by first-principles quantum mechanical simulations with Density Functional Theory (DFT). However, such simulations are...
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Examining Quality of Hand Segmentation Based on Gaussian Mixture Models
PublicationResults of examination of various implementations of Gaussian mix-ture models are presented in the paper. Two of the implementations belonged to the Intel’s OpenCV 2.4.3 library and utilized Background Subtractor MOG and Background Subtractor MOG2 classes. The third implementation presented in the paper was created by the authors and extended Background Subtractor MOG2 with the possibility of operating on the scaled version of...
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Active Learning on Ensemble Machine-Learning Model to Retrofit Buildings Under Seismic Mainshock-Aftershock Sequence
PublicationThis research presents an efficient computational method for retrofitting of buildings by employing an active learning-based ensemble machine learning (AL-Ensemble ML) approach developed in OpenSees, Python and MATLAB. The results of the study shows that the AL-Ensemble ML model provides the most accurate estimations of interstory drift (ID) and residual interstory drift (RID) for steel structures using a dataset of 2-, to 9-story...
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Global Optimization for Recovery of Clipped Signals Corrupted With Poisson-Gaussian Noise
PublicationWe study a variational formulation for reconstructing nonlinearly distorted signals corrupted with a Poisson-Gaussian noise. In this situation, the data fidelity term consists of a sum of a weighted least squares term and a logarithmic one. Both of them are precomposed by a nonlinearity, modelling a clipping effect, which is assumed to be rational. A regularization term, being a piecewise rational approximation of the ℓ0 function...
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Utility of an unitary-shredding method to evaluate the conditions and selection of constructional features during grinding
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Quantum superadditivity in linear optics networks: Sending bits via multiple-access Gaussian channels
PublicationSuperadditivity effects of communication capacities are known in the case of discrete variable quantum channels. We describe the continuous variable analog of one of these effects in the framework of Gaussian multiple access channels (MACs). Classically, superadditivity-type effects are strongly restricted: For example, adding resources to one sender is never advantageous to other senders in sending their respective information...
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Non-Gaussian Resistance Fluctuations in Gold-Nanoparticle-Based Gas Sensors: An Appraisal of Different Evaluation Techniques
PublicationVolatile organic compounds, such as formaldehyde, can be used as biomarkers in human exhaled breath in order to non-invasively detect various diseases, and the same compounds are of much interest also in the context of environmental monitoring and protection. Here, we report on a recently-developed gas sensor, based on surface-functionalized gold nanoparticles, which is able to generate voltage noise with a distinctly non-Gaussian...
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Study of preference for surround microphone techniques, used in the recording of choir and instrumental ensemble
PublicationThe aim of this paper is to describe the process of choosing the best surround microphone technique for recording of choir with an instrumental ensemble. First, examples of multichannel microphone techniques including those used in the recording are described. Then, the assumptions and details of music recording in Radio Gdansk Studio are provided as well as the process of mixing of the multichannel recording. The extensive subjective...
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Fault detection and diagnostics of complex dynamic systems using Gaussian Process Models - nuclear power plant case study
PublicationThe article examines the use of Gaussian Process Models to simulate the dynamic processes of a Pressurized Water nuclear Reactor for fault detection and diagnostics. The paper illustrates the potential of Gaussian Process Models as a tool for monitoring and predicting various fault conditions in Pressurized Water nuclear Reactor power plants, including reactor coolant flow and temperature variations, deviations from nominal working...
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Segmentation-Based BI-RADS ensemble classification of breast tumours in ultrasound images
PublicationBackground: The development of computer-aided diagnosis systems in breast cancer imaging is exponential. Since 2016, 81 papers have described the automated segmentation of breast lesions in ultrasound images using arti- ficial intelligence. However, only two papers have dealt with complex BI-RADS classifications. Purpose: This study addresses the automatic classification of breast lesions into binary classes (benign vs. ma- lignant)...
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Ensemble Classifier for Mining Data Streams
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Detection and segmentation of moving vehicles and trains using Gaussian mixtures, shadow detection and morphological processing
PublicationSolution presented in this paper combines background modelling, shadow detection and morphological and temporal processing into one system responsible for detection and segmentation of moving objects recorded with a static camera. Vehicles and trains are detected based on their pixellevel difference from the continually updated background model utilizing a Gaussian mixture calculated separately for every pixel. The shadow detection...
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Oriented Gaussian beams for high-accuracy computation with accuracy control of X-ray propagation through a multi-lens system
PublicationA highly accurate method for calculating X-ray propagation is developed. Within this approach, the propagating wave is represented as a superposition of oriented Gaussian beams. The direction of wave propagation in each Gaussian beam agrees with the local direction of propagation of the X-ray wavefront. When calculating the propagation of X-ray waves through lenses, the thin lens approximation is applied. In this approximation,...
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Sampling-based novel heterogeneous multi-layer stacking ensemble method for telecom customer churn prediction
PublicationIn recent times, customer churn has become one of the most significant issues in business-oriented sectors with telecommunication being no exception. Maintaining current customers is particularly valuable due to the high degree of rivalry among telecommunication companies and the costs of acquiring new ones. The early prediction of churned customers may help telecommunication companies to identify the causes of churn and design...
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Gaussian mixture decomposition in the analysis of MALDI-TOF spectra
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Optimal asynchronous estimation of 2D Gaussian-Markov processes
PublicationW artykule rozważa się problem estymacji trajektorii dwuwymiarowych ciągłoczasowych procesów Gaussa-Markowa na podstawie zaszumionych pomiarów wykonywanych w nierównomiernie rozłożonych chwilach czasu. W przypadku takiego problemu, w każdym cyklu pracy algorytmu należy dokonać dyskretnoczasowej predykcji (analogicznie jak w przypadku filtru Kalmana). Niestety zadanie to może być złożone obliczeniowo. Aby rozwiązać ten problem,...
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Agent-Based Data Reduction Using Ensemble Technique
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EBE: elastic blob ensemble for coarse human tracking
PublicationProponujemy nowy probabilistyczny algorytm śledzenia oparty na elastycznym zespole kropelkowym (EBE), który ma zastosowanie przy śledzeniu obiektów elastycznych. Wynikiem jest wskazówka nt. zgrubnego ruchu w postaci lokalizacji i orientacji obiektu wraz z lokalizacją kropelki. Głównym założeniem jest to, że orientacja całego obiektu nie zmienia się znacznie między sąsiednimi klatkami. Dyskretna przestrzeń rozwiązań jest tworzona...
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Satellite Image Classification Using a Hierarchical Ensemble Learning and Correlation Coefficient-Based Gravitational Search Algorithm
PublicationSatellite image classification is widely used in various real-time applications, such as the military, geospatial surveys, surveillance and environmental monitoring. Therefore, the effective classification of satellite images is required to improve classification accuracy. In this paper, the combination of Hierarchical Framework and Ensemble Learning (HFEL) and optimal feature selection is proposed for the precise identification...
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Gaussian Mixture Decomposition of Time-Course DNA Microarray Data
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SMOTE-Based Homogeneous Ensemble Methods for Software Defect Prediction
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Ensemble-Based Logistic Model Trees for Website Phishing Detection
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Heterogeneous Ensemble with Combined Dimensionality Reduction for Social Spam Detection
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The detection of Alternaria solani infection on tomatoes using ensemble learning
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Fault diagnosis of marine 4-stroke diesel engines using a one-vs-one extreme learning ensemble
PublicationThis paper proposes a novel approach for intelligent fault diagnosis for stroke Diesel marine engines, which are commonly used in on-road and marine transportation. The safety and reliability of a ship's work rely strongly on the performance of such an engine; therefore, early detection of any type of failure that affects the engine is of crucial importance. Automatic diagnostic systems are of special importance because they can...
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DIAGNOSIS OF MALIGNANT MELANOMA BY NEURAL NETWORK ENSEMBLE-BASED SYSTEM UTILISING HAND-CRAFTED SKIN LESION FEATURES
PublicationMalignant melanomas are the most deadly type of skin cancer but detected early have high chances for successful treatment. In the last twenty years, the interest of automated melanoma recognition detection and classification dynamically increased partially because of public datasets appearing with dermatoscopic images of skin lesions. Automated computer-aided skin cancer detection in dermatoscopic images is a very challenging task...
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Improving peak detection by Gaussian mixture modeling of mass spectral signal
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Analyze of Maldi-TOF Proteomic Spectra with Usage of Mixture of Gaussian Distributions
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Solvent Screening for Solubility Enhancement of Theophylline in Neat, Binary and Ternary NADES Solvents: New Measurements and Ensemble Machine Learning
PublicationTheophylline, a typical representative of active pharmaceutical ingredients, was selected to study the characteristics of experimental and theoretical solubility measured at 25 °C in a broad range of solvents, including neat, binary mixtures and ternary natural deep eutectics (NADES) prepared with choline chloride, polyols and water. There was a strong synergistic effect of organic solvents mixed with water, and among the experimentally...
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Underground Water Level Prediction in Remote Sensing Images Using Improved Hydro Index Value with Ensemble Classifier
PublicationThe economic sustainability of aquifers across the world relies on accurate and rapid estimates of groundwater storage changes, but this becomes difficult due to the absence of insitu groundwater surveys in most areas. By closing the water balance, hydrologic remote sensing measures offer a possible method for quantifying changes in groundwater storage. However, it is uncertain to what extent remote sensing data can provide an...
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Variable‐fidelity modeling of antenna input characteristics using domain confinement and two‐stage Gaussian process regression surrogates
PublicationThe major bottleneck of electromagnetic (EM)-driven antenna design is the high CPU cost of massive simulations required by parametric optimization, uncertainty quantification, or robust design procedures. Fast surrogate models may be employed to mitigate this issue to a certain extent. Unfortunately, the curse of dimensionality is a serious limiting factor, hindering the construction of conventional data-driven models valid over...
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Acousto-optic interaction of a Gaussian laser beam with an ultrasonic wave of cylindrical symmetry
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Adaptive filtering of microarray gene expression data based on Gaussian mixture decomposition
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Signal Partitioning Algorithm for Highly Efficient Gaussian Mixture Modeling in Mass Spectrometry
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Higher-order spectra for harmonics detection in nonlinear systems at presence of Gaussian noise.
PublicationPrzedstawiono metodę wykrywania harmonicznych w ukladach nieliniowych za pomocą funkcji bispektrum. Przebadano skuteczność proponowanej metody w porównaniu z metodą wykorzystującą gęstość widmową mocy. Badania przeprowadzono dla sygnałów będących sumą sygnału harmonicznego i realizacji szumu białego.
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Ergodic type theorems for Gaussian systemstwierdzenia typu ergodycznego dla układów gaussowskich
PublicationUdowodniono twierdzenie typu ergodycznego dla zmiennych losowych będących złożeniem zmiennych losowych gaussowskich z funkcjami z odpowiedniej klasy.
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Tree-based homogeneous ensemble model with feature selection for diabetic retinopathy prediction
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Multidimensional Feature Selection and Interaction Mining with Decision Tree Based Ensemble Methods
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Ensemble Online Classifier Based on the One-Class Base Classifiers for Mining Data Streams
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Likelihood of Transformation to Green Infrastructure Using Ensemble Machine Learning Techniques in Jinan, China
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Comparison of single best artificial neural network and neural network ensemble in modeling of palladium microextraction
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Initializing the EM Algorithm for Univariate Gaussian, Multi-Component, Heteroscedastic Mixture Models by Dynamic Programming Partitions
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