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Wyniki wyszukiwania dla: BAYESIAN REGULARIZATION
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Wyrażanie niepewności za pomocą przedziałów
PublikacjaZ perspektywy dwóch różnych interpretacji prawdopodobieństwa - klasycznej (częstościowej) i subiektywnej (bayesowskiej) oraz propozycji nowego przewodnika ustalającego zasady obliczania i wyrażania niepewności pomiaru (GUM), porównano sposoby komunikowania niepewności za pomocą przedziałów: ufności, bayesowskiego, objęcia, rozszerzenia.
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Optimally regularized local basis function approach to identification of time-varying systems
PublikacjaAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state of the art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
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Application possibilities of LBN for civil engineering issues
PublikacjaBayesian Networks (BN) are efficient to represent knowledge and for the reasoning in uncertainty. However the classic BN requires manual definition of the network structure by an expert, who also defines the values entered into the conditional probability tables. In practice, it can be time-consuming, hence the article proposes the use of Learning Bayesian Networks (LBN). The aim of the study is not only to present LBN, which can...
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Adaptive identification of sparse underwater acoustic channels with a mix of static and time-varying parameters
PublikacjaWe consider identification of sparse linear systems with a mix of static and time-varying parameters. Such systems are typical in underwater acoustics (UWA), for instance, in applications requiring identi- fication of the acoustic channel, such as UWA communications, navigation and continuous-wave sonar. The recently proposed fast local basis function (fLBF) algorithm provides high performance when identi- fying time-varying systems....
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Deep Learning Basics 2023/24
Kursy OnlineA course about the basics of deep learning intended for students of Computer Science. It includes an introduction to supervised machine learning, the architecture of basic artificial neural networks and their training algorithms, as well as more advanced architectures (convolutional networks, recurrent networks, transformers) and regularization and optimization techniques.
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Soft-decision schemes for radar estimation of elevation at low grazing angles
PublikacjaIn modern radars, the problem of estimating elevation angle at low grazing angles is typically solved using superresolution techniques. These techniques often require one to provide an estimate of the number of waveforms impinging the array, which one can accomplish using model selection techniques. In this paper, we investigate the performance of an alternative approach, based on the Bayesian-like model averaging. The Bayesian...
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Vibration testing in buildings and safety of their operation
PublikacjaThe paper presents the issue of vibrations in residential buildings located near roads. It describes the measurement methodology and criteria for assessing the impact of vibrations generated by passing trucks. The article specifies a method to establish the impact on the operation of the examined facilities and it promotes the idea of employing a Bayesian network to determine probabilistically the level of risk to single-family...
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Wireless LAN with noncooperative anonymous stations: QOS provisioning via war of attrition
PublikacjaMAC-layer QoS provision necessitates an admission scheme to grant a requested QoS notwithstanding subse-quent requests. For an ad hoc WLAN with anonymous stations, we assume a degree of power awareness to propose a session- rather than frame-level bidding for bandwidth. Next we analyze the underlying Bayesian war of attrition game.
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Broadcast copies reveal the quantumness of correlations
PublikacjaWe study the quantumness of bipartite correlations by proposing a quantity that combines a measure of total correlations-mutual information-with the notion of broadcast copies-i.e., generally nonfactorized copies-of bipartite states. By analyzing how our quantity increases with the number of broadcast copies, we are able to classify classical, separable, and entangled states. This motivates the definition of the broadcast regularization...
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Quantum corrections to quasi-periodic solution of Sine-Gordon model and periodic solution of phi^4 model
PublikacjaAnalytical form of quantum corrections to quasi-periodic solution of Sine-Gordon model and periodic solution of phi^4 model is obtained through zeta function regularisation with account of all rest variables of a d-dimensional theory. Qualitative dependence of quantum corrections on parameters of the classical systems is also evaluated for a much broader class of potentials u(x) = b^2 f(bx) + C with b and C as arbitrary real constants
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Medley filters - simple tools for efficient signal smoothing
PublikacjaMedley filters are defined as convex combinations of elementary smoothing filters (averaging, median) with different smoothing bandwidths. It is shown that when adaptive weights of such a mixture are evaluated using the recently proposed Bayesian rules, one obtains a tool which often outperforms the state-of-the-art wavelet-based smoothing algorithms. Additionally, unlike wavelet-based procedures, medley filters can easily cope...
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Identification of Fast Time-varying Communication Channels Using the Preestimation Technique
PublikacjaAccurate identification of stochastic systems with fast-varying parameters is a challenging task which cannot be accomplished using model-free estimation methods, such as weighted least squares, which assume only that system coefficients can be regarded as locally constant. The current state-of-the-art solutions are based on the assumption that system parameters can be locally approximated by a linear combination of appropriately...
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Regularized Local Basis Function Approach to Identification of Nonstationary Processes
PublikacjaThe 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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Global Optimization for Recovery of Clipped Signals Corrupted With Poisson-Gaussian Noise
PublikacjaWe 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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Limiting distribution of the three-state semi-Markov model of technical state transitions of ship power plant machines and its applicability in operational decision-making.
PublikacjaThe article presents the three-state semi-Markov model of the process {W(t): t 0} of state transitions of a ship power plant machine, with the following interpretation of these states: s1 – state of full serviceability, s2 – state of partial serviceability, and s3 – state of unserviceability. These states are precisely defined for the ship main engine (ME). A hypothesis is proposed which explains the possibility of application...
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A Model for Risk Assessment and Management of Construction Projects in Urban Conditions
PublikacjaThe authors are seeking new methods for improving the efficiency of the investments associated with the maintenance and operation of existing civil engineering structures. It is demonstrated how the knowledge about the elements of construction and operation phases and their relationships, combined with monitoring data can be used for more effective management of the risks associated with civil engineering projects. The methodology...
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On autoregressive spectrum estimation using the model averaging technique
PublikacjaThe problem of estimating spectral density of a nonstationary process satisfying local stationarity conditions is considered. The proposed solution is a two step procedure based on local autoregressive (AR) modeling. In the first step Bayesian-like averaging of AR models, differing in order, is performed. The main contribution of the paper is development of a new final-prediction-error-like statistic, which can be used to select...
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A simple test for quantum channel capacity
PublikacjaBased on state and channel isomorphism we point out that semidefiniteprogramming can be used as a quick test for nonzero one-way quantum channelcapacity. This can be achieved by searching for symmetric extensions of statesisomorphic to a given quantum channel. With this method we provide examplesof quantum channels that can lead to high entanglement transmission but stillhave zero one-way capacity, in particular, regions of symmetric...
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Comparing Arbitrary Unrooted Phylogenetic Trees Using Generalized Matching Split Distance
PublikacjaIn the paper, we describe a method for comparing arbitrary, not necessary fully resolved, unrooted phylogenetic trees. Proposed method is based on finding a minimum weight matching in bipartite graphs and can be regarded as a generalization of well-known Robinson-Foulds distance. We present some properties and advantages of the new distance. We also investigate some properties of presented distance in a common biological problem...
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Music Data Processing and Mining in Large Databases for Active Media
PublikacjaThe aim of this paper was to investigate the problem of music data processing and mining in large databases. Tests were performed on a large data-base that included approximately 30000 audio files divided into 11 classes cor-responding to music genres with different cardinalities. Every audio file was de-scribed by a 173-element feature vector. To reduce the dimensionality of data the Principal Component Analysis (PCA) with variable...
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Measurement Campaign and Mathematical Model Construction for the Ship Zodiak Magnetic Signature Reproduction
PublikacjaThe paper presents the partial work done within the framework of the EDA Siramis II project focused on magnetic signature reproduction of ships. Reproduction is understood here as the ability to determine the magnetic anomaly of the local Earth magnetic field in any direction and at any measurement depth due to the presence of the analysed object. The B-91 type hydrographic ship Zodiak was selected as the real case study. The work...
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Expert systems in assessing the construction process safety taking account of the risk of disturbances
PublikacjaThe objective of the paper is to present the issue of safety manage-ment during the construction process. Threats in the form of disturb-ances may occur in the preparatory phase, during the execution of the construction project and also during its operational use. The arti-cle presents the concept of applying the methodology based, among others, on Learning Bayesian Networks, Artificial Neural Networks and Support Vector Machine,...
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Locally Adaptive Cooperative Kalman Smoothing and Its Application to Identification of Nonstationary Stochastic Systems
PublikacjaOne of the central problems of the stochastic approximation theory is the proper adjustment of the smoothing algorithm to the unknown, and possibly time-varying, rate and mode of variation of the estimated signals/parameters. In this paper we propose a novel locally adaptive parallel estimation scheme which can be used to solve the problem of fixed-interval Kalman smoothing in the presence of model uncertainty. The proposed solution...
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Machine Learning in Multi-Agent Systems using Associative Arrays
PublikacjaIn this paper, a new machine learning algorithm for multi-agent systems is introduced. The algorithm is based on associative arrays, thus it becomes less complex and more efficient substitute of artificial neural networks and Bayesian networks, which is confirmed by performance measurements. Implementation of machine learning algorithm in multi-agent system for aided design of selected control systems allowed to improve the performance...
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Adapt Your Teacher: Improving Knowledge Distillation for Exemplar-free Continual Learning
PublikacjaIn this work, we investigate exemplar-free class incremental learning (CIL) with knowledge distillation (KD) as a regularization strategy, aiming to prevent forgetting. KDbased methods are successfully used in CIL, but they often struggle to regularize the model without access to exemplars of the training data from previous tasks. Our analysis reveals that this issue originates from substantial representation shifts in the teacher...
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Identification of nonstationary multivariate autoregressive processes– Comparison of competitive and collaborative strategies for joint selection of estimation bandwidth and model order
PublikacjaThe problem of identification of multivariate autoregressive processes (systems or signals) with unknown and possibly time-varying model order and time-varying rate of parameter variation is considered and solved using parallel estimation approach. Under this approach, several local estimation algorithms, with different order and bandwidth settings, are run simultaneously and compared based on their predictive performance. First,...
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Risk Diagnosis and Management with BBN for Civil Engineering Projects during Construction and Operation
PublikacjaThe authors demonstrate how expert knowledge about the construction and operation phases combined with monitoring data can be utilized for the diagnosis and management of risks typical to large civil engineering projects. The methodology chosen for estimating the probabilities of risk elements is known as Bayesian Belief Networks (BBN). Using a BBN model one can keep on updating the risk event probabilities as the new evidence...
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Application of BN in Risk Diagnostics Arising from the Degree of Urban Regeneration Area Degradation
PublikacjaUrban regeneration as a complex project, generates many extremely specific threats affecting the increase of investment risk. Its unique nature causes that probability parameter, normally applied in the process of risk quantification, is extremely difficult to estimate. Due to lack of historical data urban regeneration related activities are therefore associated with uncertainty. According to the authors, a useful tool for resolving...
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Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation
PublikacjaIn this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic model,...
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A probabilistic-driven framework for enhanced corrosion estimation of ship structural components
PublikacjaThe 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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Genre-Based Music Language Modeling with Latent Hierarchical Pitman-Yor Process Allocation
PublikacjaIn this work we present a new Bayesian topic model: latent hierarchical Pitman-Yor process allocation (LHPYA), which uses hierarchical Pitman-Yor pr ocess priors for both word and topic distributions, and generalizes a few of the existing topic models, including the latent Dirichlet allocation (LDA), the bi- gram topic model and the hierarchical Pitman-Yor topic model. Using such priors allows for integration of -grams with a topic...
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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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Size effect in concrete beams under bending – influence of the boundary layer and the numerical description of cracks
PublikacjaIn the paper the size effect phenomenon in concrete is analysed. The results of numerical simulations of using FEM on geometrically similar un-notched and notched concrete beams under bending are presented. Concrete beams of four different sizes and five different notch heights under three-point bending test were simulated. In total 18 beams were analysed. Two approaches were used to describe cracks in concrete. First, eXtended...
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Diagnosis´ likelihood and diagnosis rightness about the technical state of diesel engine
PublikacjaW referacie uzasadniono potrzebę rozróżniania pojęć "wiarygodność diagnozy" i "trafność diagnozy" przy podejmowaniu decyzji eksploatacyjnych. Wyprowadzono wzór na prawdopodobieństwo sformułowania diagnozy jako miary wiarygodności diagnozy. Do wyprowadzenia tego wzoru zastosowano teorię procesów semimarkowskich oraz wzór Bayesa na prawdopodobieństwo warunkowe.
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Theory versus experiment for vacuum Rabi oscillations in lossy cavities. II. Direct test of uniqueness of vacuum
PublikacjaThe paper continues the analysis of vacuum Rabi oscillations we started in part I [Phys. Rev. A 79, 033836 (2009)]. Here we concentrate on experimental consequences for cavity QED of two different classes of representations of harmonic-oscillator Lie algebras. The zero-temperature master equation, derived in part I for irreducible representations of the algebra, is reformulated in a reducible representation that models electromagnetic...
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On some problems in determining tensile parameters of concrete model from size effect tests
PublikacjaThe paper presents results of numerical simulations of size effect phenomenon in concrete specimens. The behaviour of in-plane geometrically similar notched and unnotched beams under three-point bending is investigated. In total 18 beams are analysed. Concrete beams of four different sizes and five different notch to depth ratios are simulated. Two methods are applied to describe cracks. First, an elasto-plastic constitutive law...
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A Comprehensive Analysis of Deep Neural-Based Cerebral Microbleeds Detection System
PublikacjaMachine learning-based systems are gaining interest in the field of medicine, mostly in medical imaging and diagnosis. In this paper, we address the problem of automatic cerebral microbleeds (CMB) detection in magnetic resonance images. It is challenging due to difficulty in distinguishing a true CMB from its mimics, however, if successfully solved it would streamline the radiologists work. To deal with this complex three-dimensional...
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Magnetic Signature Description of Ellipsoid-Shape Vessel Using 3D Multi-Dipole Model Fitted on Cardinal Directions
PublikacjaThe article presents a continuation of the research on the 3D multi-dipole model applied to the reproduction of magnetic signatures of ferromagnetic objects. The model structure has been modified to improve its flexibility - model parameters determined by optimization can now be located in the cuboid contour representing the object's hull. To stiffen the model, the training dataset was expanded to data collected from all four cardinal...
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Zastosowanie wiarygodności diagnozy do podejmowania decyzji w procesie eksploatacji urządzeń
PublikacjaUzasadniono potrzebę rozróżniania pojęć wiarygodność diagnozy i trafność diagnozy. Wyprowadzono wzór na prawdopodobieństwo sformułowania prawidłowej diagnozy jako miarę wiarygodności diagnozy. Do wyprowadzenia tego wzoru zastosowano teorię procesów semimarkowskich oraz postulat T. Bayesa dotyczący prawdopodobieństwa warunkowego. Przedstawiona została także możliwość zastosowania wiarygodności diagnozy w procesie podejmowania racjonalnych...
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Coupling between Blood Pressure and Subarachnoid Space Width Oscillations during Slow Breathing
PublikacjaThe precise mechanisms connecting the cardiovascular system and the cerebrospinal fluid (CSF) are not well understood in detail. This paper investigates the couplings between the cardiac and respiratory components, as extracted from blood pressure (BP) signals and oscillations of the subarachnoid space width (SAS), collected during slow ventilation and ventilation against inspiration resistance. The experiment was performed on...
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Data-driven, probabilistic model for attainable speed for ships approaching Gdańsk harbour
PublikacjaThe growing demand for maritime transportation leads to increased traffic in ports. From this arises the need to observe the consequences of the specific speed ships reach when approaching seaports. However, usually the analyzed cases refer only to the statistical evaluation of the studied phenomenon or to the empirical modelling, ignoring the mutual influence of variables such as ship type, length or weather conditions. In this...
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Selecting cost-effective risk control option for advanced maritime operations; Integration of STPA-BN-Influence diagram
PublikacjaAdvanced maritime operations, such as remote pilotage, are vulnerable to new emergent risks due to increased system complexity and a multitude of interactions. Thus, maritime researchers this decade have combined Systems-Theoretic Process Analysis (STPA) and Bayesian Network (BN) to effectively manage these risks. Although these methods are effective in identifying hazards and analyzing risk levels, none of the STPA-BN studies...
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Metody analizy ryzyka podejmowania błędnych decyzji z powodu niepewności pomiarów
PublikacjaReferat dotyczy sposobów definiowania ryzyka podejmowania błędnych decyzji z powodu niepewności pomiarów oraz metod jego obliczania. Usystematyzowano rodzaje prawdopodobieństw łącznych i warunkowych stosowanych jako miary ryzyka w kontekście procesów produkcyjnych. Dokonano przeglądu metod obliczania ryzyka, ze szczególnym uwzględnieniem metod Bayesowskich. Zwrócono uwagę na różnice w stosowanych probabilistycznych modelach pomiaru...
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On Improved-Reliability Design Optimization of High-Frequency Structures Using Local Search Algorithms
PublikacjaThe role of numerical optimization has been continuously growing in the design of high-frequency structures, including microwave and antenna components. At the same time, accurate evaluation of electrical characteristics necessitates full-wave electromagnetic (EM) analysis, which is CPU intensive, especially for complex systems. As rigorous optimization routines involve repetitive EM simulations, the associated cost may be significant....
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Instrument detection and pose estimation with rigid part mixtures model in video-assisted surgeries
PublikacjaLocalizing 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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WHY SHOULD WE ADOPT NON-USED ATTICS OF MONUMENTAL SACRAL CATHOLIC CHURCHES FOR SECULAR PURPOSES?
PublikacjaA motive for adapting the desecrated churches to new purposes is a broadly discussed matter, progressively better investigated and defined. Is it advisable to introduce a new, permanent function, complementary to the sacred one in the historical ecclesial buildings? This paper presents the results of the research on benefits of adapting the non-utilized attics of monumental churches still performing their sacred function, located...
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Synagogi dawnej Polski - ich teraźniejszość i przyszłość
PublikacjaTekst stanowi próbę ujęcia w szerszej perspektywie złożonego zjawiska zmiany formy użytkowania ocalałych obiektów kultu religijnego. Postępująca sekularyzacja współczesnych społeczeństw stanowi wyzwanie dla religijnych społeczności różnych wyznań, przynosząc również pytania dotyczące zmiany przeznaczenia pustoszejących świątyń. Biorąc pod uwagę społeczny kontekst zarysowany powyżej, ocalałe budynki synagog można uznać za odrębny,...
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Improved Modeling of Microwave Structures Using Performance-Driven Fully-Connected Regression Surrogate
PublikacjaFast replacement models (or surrogates) have been widely applied in the recent years to accelerate simulation-driven design procedures in microwave engineering. The fundamental reason is a considerable—and often prohibitive—CPU cost of massive full-wave electromagnetic (EM) analyses related to solving common tasks such as parametric optimization or uncertainty quantification. The most popular class of surrogates are data-driven...
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Game Theory Analysis of Bidding for a Construction Contract
PublikacjaThe authors are concerned with a bidding problem. There are two companies (P1 and P2) bidding for a highway construction project. In order to be more competitive, P1 considers buying a new gravel pit near the construction site. The basic cost of the pit is known to both companies. However, there is also an additional, hidden, cost (C) known only to P1. P2 is uncertain whether the hidden cost is C = 0 or C = x. P1 plans to bid for...
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Probability measures of likelihood of diagnosis of the technical state of main combustion engines of sea-going ships
PublikacjaW artykule uzasadniono potrzebę rozróżniania pojęć wiarygodności diagnozy i trafności diagnozy przy podejmowaniu decyzji eksploatacyjnych. Wyprowadzono wzór na prawdopodobieństwo sformułowania prawidłowej diagnozy jako miary wiarygodności diagnozy. Do wyprowadzenia tego wzoru zastosowano teorię procesów semimarkowskich oraz wzór Bayesa na prawdopodobieństwo warunkowe. Podano także inne probabilistyczne miary wiarygodności diagnozy....