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Wyświetlanie 1-15 z 127
Tytuł:
Finitely additive functions in measure theory and applications
Autorzy:
Alpay, Daniel
Jorgensen, Palle
Powiązania:
https://bibliotekanauki.pl/articles/29519748.pdf
Data publikacji:
2024
Wydawca:
Akademia Górniczo-Hutnicza im. Stanisława Staszica w Krakowie. Wydawnictwo AGH
Tematy:
Hilbert space
reproducing kernel
probability space
Gaussian field
transforms
covariance
Itô integration
Itô calculus
generalized Brownian motion
Opis:
In this paper, we consider, and make precise, a certain extension of the Radon–Nikodym derivative operator, to functions which are additive, but not necessarily sigma-additive, on a subset of a given sigma-algebra. We give applications to probability theory; in particular, to the study of μ-Brownian motion, to stochastic calculus via generalized Itô-integrals, and their adjoints (in the form of generalized stochastic derivatives), to systems of transition probability operators indexed by families of measures μ, and to adjoints of composition operators.
Źródło:
Opuscula Mathematica; 2024, 44, 3; 323-339
1232-9274
2300-6919
Pojawia się w:
Opuscula Mathematica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A hybrid evolutionary algorithm of optimized controller placement in SDN environment
Autorzy:
Hemagowri, J.
Tamil Selvan, P.
Powiązania:
https://bibliotekanauki.pl/articles/38704829.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
controller
software defined network
Gaussian chaotic map
fish swarm
multi-criteria optimization
kontroler
sieć zdefiniowana programowo
mapa chaosu Gaussa
rój ryb
optymalizacja wielokryterialna
Opis:
Controller placement problem (CPP) is a significant technological challenge in software defined network (SDN). Deployment of a properly designed SDN-based network is required to detect optimal number of controllers for enhancing the network’s performance. However, the best possible controller placement for enhancing the network’s performance faces many issues. To solve the CPP, a novel technique called the hybrid evolutionary algorithm of optimized controller placement (HEA-OCP) in SDN environment is introduced to increase network’s performance by different network topologies. In the proposed model, optimized controller placement using improved multi-objective artificial fish optimization is employed to improve data transmission and reduce latency. Controller placement can be determined using an undirected graph based on a variety of factors, including propagation delay, load balancing capabilities and bandwidth, fault tolerance and data transfer rate, and a variety of other factors. For each controller, the fitness value is calculated over multi-criteria functions. The optimizer’s performance can be improved with the use of Gaussian chaotic maps. In large-scale SDN networks using HEC-OCP, the algorithm dynamically analyzes the optimal number of controllers and the best connections between switches and controllers. As a result, the overall network performance is improved and the delay minimization-based controller placement strategy is obtained. The simulation of HEA-OCP with existing methods is conducted by a network topology dataset of various metrics, namely packet delivery ratio, packet drop rate, throughput, average latency, and jitter. The proposed HEA-OCP improves the packet delivery and throughput with reduced average latency, and packet drop ensures more instantaneous communications in real-time applications of SDN for better decision-making.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 4; 539-556
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A probabilistic approach for approximation of optical and opto-electronic properties of an opto-semiconductor wafer under consideration of measuring inaccuracy and model uncertainty
Autorzy:
Stroka, Stefan M.
Heumann, Christian
Suhrke, Fabian
Meindl, Kathrin
Powiązania:
https://bibliotekanauki.pl/articles/2204192.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Stowarzyszenie Elektryków Polskich
Tematy:
Gaussian process regression
machine learning
uncertainty quantification
photoluminescence
opto-semiconductor wafer measuring
Opis:
This paper presents a probabilistic machine learning approach to approximate wavelength values for unmeasured positions on an opto-semiconductor wafer after epitaxy. Insufficient information about optical and opto-electronic properties may lead to undetected specification violations and, consequently, to yield loss or may cause product quality issues. Collection of information is restricted because physical measuring points are expensive and in practice samples are only drawn from 120 specific positions. The purpose of the study is to reduce the risk of uncertainties caused by sampling and measuring inaccuracy and provide reliable approximations. Therefore, a Gaussian process regression is proposed which can determine a point estimation considering measuring inaccuracy and further quantify estimation uncertainty. For evaluation, the proposed method is compared with radial basis function interpolation using wavelength measurement data of 6-inch InGaN wafers. Approximations of these models are evaluated with the root mean square error. Gaussian process regression with radial basis function kernel reaches a root mean square error of 0.814 nm averaged over all wafers. A slight improvement to 0.798 nm could be achieved by using a more complex kernel combination. However, this also leads to a seven times higher computational time. The method further provides probabilistic intervals based on means and dispersions for approximated positions.
Źródło:
Opto-Electronics Review; 2023, 31, 2; art. no. e145863
1230-3402
Pojawia się w:
Opto-Electronics Review
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An Adaptive Richardson-Lucy Algorithm for Medical Image Restoration
Autorzy:
Yaqoub, Qunoot A.
Al-Ani, Ayad A.
Powiązania:
https://bibliotekanauki.pl/articles/2200960.pdf
Data publikacji:
2023
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
constraint least square filter
Gaussian blurring function
Gaussian noise function
inverse filter
non-blind deconvolution
point spread function
Richardson-Lucy algorithm
Wiener filter
Opis:
Image restoration is the process of estimating the original image content from a degraded picture. In this paper, the Richardson-Lucy iterative algorithm was developed to improve the quality of degraded medical images. It has been assumed that medical images are exposed to two types of degradation. The first type is the blur function in the Gaussian form with different widths, i.e. σ = 1 , 2, and 3. The second type of degradation was assumed to be of the independent white Gaussian noise type with different signal-to-noise ratio values: SNR = 10, 50 , and 100. The results obtained from the adaptive filter are compared, quantitatively, with different conventional filters: inverse, Wiener, and constraint least square, by applying different measures, such as: power signal to noise ratio (PSNR), structural similarity index (SSID), and root mean square error (RMSE). The comparison showed that the adaptive recovery filter achieves better results.
Źródło:
Journal of Telecommunications and Information Technology; 2023, 1; 66--77
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fault detection in photovoltaic systems using the inverse of the belonging individual Gaussian probability
Autorzy:
Sendjasni, Salah
Yagoubi, Benabdellah
Daoud, Mohamed
Belbachir, Nasreddine
Ziane, Abderrezzaq
Powiązania:
https://bibliotekanauki.pl/articles/2174471.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Polskie Towarzystwo Diagnostyki Technicznej PAN
Tematy:
photovoltaic systems
faults
infrared image
Gaussian white noise
inverse probability
system fotowoltaiczny
uszkodzenie
obraz termowizyjny
Opis:
This article addresses the problem of fault early detection in photovoltaic systems. In the production field, solar power plants consist of many photovoltaic arrays, which may suffer from many different types of malfunctions over time. Hence, fault early detection before it affects PV systems and leads to a full system failure is essential to monitor these systems. The fields of control and monitoring of systems have been extensively approached by many researchers using various fault detection methods. Despite all this research, to early detect and locate faults in a very large photovoltaic power plant, we must, in particular, think of an effective method that allows us to do so at the lowest costs and time. Thus, we propose a new robust technique based on the inverse of the belonging individual Gaussian probability (IBIGP) to early detect and locate faults in the power curve as well as in the Infrared image of the photovoltaic systems. While most fault detection methods are well incorporated in other domains, the IBIGP technique is still in its infancy in the photovoltaic field. We will show, however, in this work that the IBIGP technique is a very promising tool for fault early detection enhancement.
Źródło:
Diagnostyka; 2023, 24, 1; art. no. 2023112
1641-6414
2449-5220
Pojawia się w:
Diagnostyka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Hybrid texture and gradient modeling for dynamic background subtraction identification systemin tobacco plant using 5G data service
Autorzy:
Gowda Thirthe, M.T.
Chandrika, J.
Powiązania:
https://bibliotekanauki.pl/articles/38699145.pdf
Data publikacji:
2023
Wydawca:
Instytut Podstawowych Problemów Techniki PAN
Tematy:
background subtraction
local binary pattern
tobacco plant
texture
Gaussian mixture model
illumination change
plant disease identification system
usuwanie tła
lokalny wzorzec binarny
tytoń
tekstura
model mieszaniny Gaussa
zmiana oświetlenia
system identyfikacji chorób roślin
Opis:
Background: Detecting the plants as objects of interest in any vision-based input sequence is highly complex due to nonlinear background objects such as rocks, shadows,etc. Therefore, it is a difficult task and an emerging one with the development of precision agriculture systems. The nonlinear variations of pixel intensity with illuminationand other causes such as blurs and poor video quality also make the object detection taskchallenging. To detect the object of interest, background subtraction (BS) is widely usedin many plant disease identification systems, and its detection rate largely depends on thenumber of features used to suppress and isolate the foreground region and its sensitivitytoward image nonlinearity. Methodology: A hybrid invariant texture and color gradient-based approach is proposed to model the background for dynamic BS, and its performance is validated byvarious real-time video captures covering different kinds of complex backgrounds and various illumination changes. Based on the experimental results, a simple multimodal featureattribute, which includes several invariant texture measures and color attributes, yieldsfinite precision accuracy compared with other state-of-art detection methods. Experimental evaluation of two datasets shows that the new model achieves superior performanceover existing results in spectral-domain disease identification model. 5G assistance: After successful identification of tobacco plant and its analysis, the finalresults are stored in a cloud-assisted server as a database that allows all kinds of 5G servicessuch as IoT and edge computing terminals for data access with valid authentication fordetailed analysis and references.
Źródło:
Computer Assisted Methods in Engineering and Science; 2023, 30, 1; 41-54
2299-3649
Pojawia się w:
Computer Assisted Methods in Engineering and Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Modelling of Li-Ion battery state-of-health with Gaussian processes
Autorzy:
Dudek, Adrian
Baranowski, Jerzy
Powiązania:
https://bibliotekanauki.pl/articles/28761940.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
lithium-ion batteries
state of health
Gaussian process
diagnostics
Opis:
The problem of lithium-ion cells, which degrade in time on their own and while used, causes a significant decrease in total capacity and an increase in inner resistance. So, it is important to have a way to predict and simulate the remaining usability of batteries. The process and description of cell degradation are very complex and depend on various variables. Classical methods are based, on the one hand, on fitting a somewhat arbitrary parametric function to laboratory data and, on the other hand, on electrochemical modelling of the physics of degradation. Alternative solutions are machine learning ones or non-parametric ones like support-vector machines or the Gaussian process (GP), which we used in this case. Besides using the GP, our approach is based on current knowledge of how to use non-parametric approaches for modeling the electrochemical state of batteries. It also uses two different ways of dealing with GP problems, like maximum likelihood type II (ML-II) methods and the Monte Carlo Markov Chain (MCMC) sampling.
Źródło:
Archives of Electrical Engineering; 2023, 72, 3; 643--659
1427-4221
2300-2506
Pojawia się w:
Archives of Electrical Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Propagation properties of partially coherent array beams with a non-uniform polarization
Autorzy:
Yang, Xianyang
Fu, Wenyu
Powiązania:
https://bibliotekanauki.pl/articles/27310095.pdf
Data publikacji:
2023
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
partially coherent
radially polarisation
Gaussian Schell-model array beams
propagation properties
Opis:
We study a new class of partially coherent array beams with a non-uniform polarization, named radially polarized Gaussian Schell-model array (RPGSMA) beams and analyze the reliability conditions for the array beams based on the unified theory of coherence and polarization, Moreover, the statistical properties of such beam propagating in free space are investigated in detail. It is found that, the propagation properties of the RPGSMA beams are closely related to initial beam parameters. With an appropriate choice of the beam parameters, the average intensity will evolve into optical lattice patterns, and the degree of coherence (DOC) from the lattice distribution on the original plane evolves into a Gaussian profile in the far field, and the degree of polarization (DOP) appears a periodical grid-like distribution on propagation. These results may be beneficial to particle trapping and free-space optical communications.
Źródło:
Optica Applicata; 2023, 53, 2; 307--319
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Transverse energy propagation and interference of elliptical Gaussian beams
Autorzy:
Li, Jin
Tan, Shuang-Cheng
Powiązania:
https://bibliotekanauki.pl/articles/27310096.pdf
Data publikacji:
2023
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
elliptical Gaussian beam
transverse energy flux
interference of EGBs
Opis:
Elliptical Gaussian beam (EGB) has many different physical properties from circular Gaussian beam. In this paper, the transverse energy flux and intensity of one and two coherent EGBs are studied. In our simulation, the transverse energy flux and intensity varying with waist ratio are discussed in detail. It has been found that through increasing the waist ratio, the transverse energy flux after interference would be strengthened significantly. Although the transverse energy flux is much weaker than the longitudinal energy flux, its signal to noise ratio has been verified to be strong enough for detection. Our derivations are still reasonable for another simulation with general experimental parameters. The simulation results are considered to be helpful for some physical experiments using the transverse energy flux of Gaussian beam, such as an important application in electromagnetic response produced by interaction of high-frequency gravitational waves.
Źródło:
Optica Applicata; 2023, 53, 2; 249--260
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A study of the Inverse Gaussian Process with hazard rate functions-based drifts applied to degradation modelling
Autorzy:
Rodríguez-Picón, Luis Alberto
Méndez-González, Luis Carlos
Pérez-Olguín, Iván JC
Hernández-Hernández, Jesús Israel
Powiązania:
https://bibliotekanauki.pl/articles/2175136.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
inverse Gaussian process
hazard rate function
degradation rate
variable drift
Opis:
The stochastic modelling of degradation processes requires different characteristics to be considered, such that it is possible to capture all the possible information about a phenomenon under study. An important characteristic is what is known as the drift in some stochastic processes; specifically, the drift allows to obtain information about the growth degradation rate of the characteristic of interest. In some phenomenon’s the growth rate cannot be considered as a constant parameter, which means that the rate may vary from trajectory to trajectory. Given this, it is important to study alternative strategies that allow to model this variation in the drift. In this paper, several hazard rate functions are integrated in the inverse Gaussian process to describe its drift in the aims of individually characterize degradation trajectories. The proposed modelling scheme is illustrated in two case studies, from which the best fitting model is selected via information criteria, a discussion of the flexibility of the proposed models is provided according to the obtained results.
Źródło:
Eksploatacja i Niezawodność; 2022, 24, 3; 590--602
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Controllable propagation of Pearcey–Gaussian beams in photorefractive media with fractional Schrödinger equation
Autorzy:
Guo, Teng
Gao, Ru
Ren, Shumin
Wang, Pengxiang
Xiao, Yan
Powiązania:
https://bibliotekanauki.pl/articles/2172852.pdf
Data publikacji:
2022
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
Pearcey-Gaussian beam
fractional Schrödinger equation
photorefractive medium
breathing soliton
Opis:
Taking the fractional Schrödinger equation as the theoretical model, the evolution behavior of the Pearcey–Gaussian beam in the photorefractive medium is studied. The results show that breathing solitons are generated when the nonlinear effect and the diffraction effect are balanced with each other. Nonlinear coefficients, Lévy index and beams amplitude affect breathing period of the soliton and maximum peak intensity. Within a certain range, the breathing period of the soliton decreases with the increase of the nonlinear coefficient and the Lévy index. However when the beams amplitude increases, the breathing period and the maximum peak intensity of the soliton increase. Under the photorefractive effect, due to the bidirectional self-acceleration property of the Pearcey beam, the solitons formed will propagate vertically. These properties can be used to manipulate the beam and have potential applications in optical switching, plasma channeling, particle manipulation, etc.
Źródło:
Optica Applicata; 2022, 52, 4; 627--638
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dynamical system of optical soliton parameters for anti-cubic and generalized anti-cubic nonlinearities with super-Gaussian and super-sech pulses
Autorzy:
Ayela, Amour Marc
Edah, Gaston
Biswas, Anjan
Zhou, Qin
Yildirim, Yakup
Khan, Salam
Alzahrani, Abdullah K.
Belic, Milivoj R.
Powiązania:
https://bibliotekanauki.pl/articles/2060685.pdf
Data publikacji:
2022
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
super-sech pulse
super-Gaussian
anti-cubic
variational approach
Opis:
The parameter dynamics of solitons, propagating through optical fibers, is emerged from the usage of variational principle. The anti-cubic nonlinearity and its generalized version are studied. This study reveals that the center position does not affect the dynamics of different parameters and only soliton power and linear momentum are conserved quantities.
Źródło:
Optica Applicata; 2022, 52, 1; 117--128
0078-5466
1899-7015
Pojawia się w:
Optica Applicata
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Gaussian process dynamic modeling and backstepping sliding mode control for magnetic levitation system of maglev train
Autorzy:
Sun, Yougang
Wang, Sumei
Lu, Yang
Xu, Junqi
Powiązania:
https://bibliotekanauki.pl/articles/2086959.pdf
Data publikacji:
2022
Wydawca:
Polskie Towarzystwo Mechaniki Teoretycznej i Stosowanej
Tematy:
maglev train
Gaussian process
sliding mode control
parameter perturbations
Opis:
The maglev trains are strongly nonlinear and open-loop unstable systems with external disturbances and parameters uncertainty. In this paper, the Gaussian process method is utilized to get the dynamic parameters, and a backstepping sliding mode controller is proposed for magnetic levitation systems (MLS) of maglev trains. That is, for a MLS of a maglev train, a nonlinear dynamic model with accurate parameters is obtained by the Gaussian process regression method, based on which a novel robust control algorithm is designed. Specifically, the MLS is divided into two sub-systems by a backstepping method. The inter virtual control inputs and the Lyapunov function are constructed in the first sub-system. For the second sub-system, the sliding mode surface is constructed to fulfil the design of the whole controller to asymptotically regulate the airgap to a desired trajectory. The stability of the proposed control method is analyzed by the Lyapunov method. Both simulation and experimental results are included to illustrate the superior performance of the presented method to cope with parameters perturbations and external disturbance.
Źródło:
Journal of Theoretical and Applied Mechanics; 2022, 60, 1; 49--62
1429-2955
Pojawia się w:
Journal of Theoretical and Applied Mechanics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Investigation of Vehicular S-LSTM NOMA Over Time Selective Nakagami-m Fading with Imperfect CSI
Autorzy:
Shankar, Ravi
Chaudhary, Bhanu Pratap
Mishra, Ritesh Kumar
Powiązania:
https://bibliotekanauki.pl/articles/2174454.pdf
Data publikacji:
2022
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
inter-symbol interference
MIMO
NOMA
orthogonal frequency division multiplexing
OFDM
S-LSTM
zero-mean circularly symmetric complex Gaussian
ZM-CSCG
Opis:
In this paper, the performance of a deep learningbased multiple-input multiple-output (MIMO) non-orthogonal multiple access (NOMA) system is investigated for 5G radio communication networks. We consider independent and identically distributed (i.i.d.) Nakagami-m fading links to prove that when using MIMO with the NOMA system, the outage probability (OP) and end-to-end symbol error rate (SER) improve, even in the presence of imperfect channel state information (CSI) and successive interference cancellation (SIC) errors. Furthermore, the stacked long short-term memory (S-LSTM) algorithm is employed to improve the system’s performance, even under time-selective channel conditions and in the presence of terminal’s mobility. For vehicular NOMA networks, OP, SER, and ergodic sum rate have been formulated. Simulations show that an S-LSTM-based DL-NOMA receiver outperforms least square (LS) and minimum mean square error (MMSE) receivers. Furthermore, it has been discovered that the performance of the end-to-end system degrades with the growing amount of node mobility, or if CSI knowledge remains poor. Simulated curves are in close agreement with the analytical results.
Źródło:
Journal of Telecommunications and Information Technology; 2022, 4; 47--59
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Preprocessing large datasets using Gaussian mixture modelling to improve prediction accuracy of truck productivity at mine sites
Autorzy:
Fan, Chengkai
Zhang, Na
Jiang, Bei
Liu, Wei Victor
Powiązania:
https://bibliotekanauki.pl/articles/2203342.pdf
Data publikacji:
2022
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
kopalnia
samochód ciężarowy
piasek roponośny
oil sands mining
mine truck productivity
Gaussian mixture model
latent variable
prediction accuracy
relative importance
Opis:
The historical datasets at operating mine sites are usually large. Directly applying large datasets to build prediction models may lead to inaccurate results. To overcome the real-world challenges, this study aimed to handle these large datasets using Gaussian mixture modelling (GMM) for developing a novel and accurate prediction model of truck productivity. A large dataset of truck haulage collected at operating mine sites was clustered by GMM into three latent classes before the prediction model was built. The labels of these latent classes generated a latent variable. Two multiple linear regression (MLR) models were then constructed, including the ordinary-MLR (O-MLR) and the hybrid GMM-MLR models. The GMM-MLR model incorporated the observed input variables and a latent variable in the form of interaction terms. The O-MLR model was the baseline model and did not involve the latent variable. The GMM-MLR model performed considerably better than the O-MLR model in predicting truck productivity. The interaction terms quantitatively measured the differences in how the observed input variables affected truck productivity in three classes (high, medium, and low truck productivity). The haul distance was the most crucial input variable in the GMM-MLR model. This study provides new insights into handling massive amounts of data in truck haulage datasets and a more accurate prediction model for truck productivity.
Źródło:
Archives of Mining Sciences; 2022, 67, 4; 661--680
0860-7001
Pojawia się w:
Archives of Mining Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
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