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Journal articles on the topic 'Stochastic sources'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

Igarashi, Sayaka, Shigehiro Sakamoto, Akemi Nishida, Ken Muramatsu, and Tsuyoshi Takada. "ICONE23-1548 STRUCTURAL RESPONSE BY GROUND MOTIONS FROM SOURCES WITH STOCHASTIC CHARACTERISTICS." Proceedings of the International Conference on Nuclear Engineering (ICONE) 2015.23 (2015): _ICONE23–1—_ICONE23–1. http://dx.doi.org/10.1299/jsmeicone.2015.23._icone23-1_252.

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2

Barchielli, Alberto, and Giancarlo Lupieri. "Photoemissive sources and quantum stochastic calculus." Banach Center Publications 43, no. 1 (1998): 53–62. http://dx.doi.org/10.4064/-43-1-53-62.

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3

Ruszkowski, Mateusz, and Mitchell C. Begelman. "Circular Polarization from Stochastic Synchrotron Sources." Astrophysical Journal 573, no. 2 (2002): 485–95. http://dx.doi.org/10.1086/340659.

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4

Wang, Wenjia, and Benjamin Haaland. "Controlling Sources of Inaccuracy in Stochastic Kriging." Technometrics 61, no. 3 (2018): 309–21. http://dx.doi.org/10.1080/00401706.2018.1514328.

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5

Shyu, M. L., S. C. Chen, and S. H. Rubin. "Stochastic Clustering for Organizing Distributed Information Sources." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 34, no. 5 (2004): 2035–47. http://dx.doi.org/10.1109/tsmcb.2004.833599.

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6

Song, Doo-Jong. "CATACLYSMIC VARIABLES : SOURCES OF STOCHASTIC GRAVITATIONAL WAVE BACKGROUND." Publications of The Korean Astronomical Society 22, no. 4 (2007): 113–32. http://dx.doi.org/10.5303/pkas.2007.22.4.113.

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7

Stoica, P., B. Ottersten, M. Viberg, and R. L. Moses. "Maximum likelihood array processing for stochastic coherent sources." IEEE Transactions on Signal Processing 44, no. 1 (1996): 96–105. http://dx.doi.org/10.1109/78.482015.

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8

Regimbau, T., and V. Mandic. "Astrophysical sources of a stochastic gravitational-wave background." Classical and Quantum Gravity 25, no. 18 (2008): 184018. http://dx.doi.org/10.1088/0264-9381/25/18/184018.

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9

Schneider, Raffaella, Stefania Marassi, and Valeria Ferrari. "Stochastic backgrounds of gravitational waves from extragalactic sources." Classical and Quantum Gravity 27, no. 19 (2010): 194007. http://dx.doi.org/10.1088/0264-9381/27/19/194007.

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10

Wu, J.-J., W. Kamleh, D. B. Leinweber, R. D. Young, and J. M. Zanotti. "Accessing high-momentum nucleons with dilute stochastic sources." Journal of Physics G: Nuclear and Particle Physics 45, no. 12 (2018): 125102. http://dx.doi.org/10.1088/1361-6471/aaeb9e.

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11

Logothetis, Andrew, Vikram Krishnamurthy, and H. Vincent Poor. "Parametric Pulse Train De-Interleaving of Stochastic Sources." IFAC Proceedings Volumes 29, no. 1 (1996): 4231–36. http://dx.doi.org/10.1016/s1474-6670(17)58345-7.

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12

Taghavi, Majid, and Kai Huang. "Stochastic capacity expansion with multiple sources of capacity." Operations Research Letters 42, no. 4 (2014): 263–67. http://dx.doi.org/10.1016/j.orl.2014.04.005.

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13

Caprini, Chiara. "Stochastic background of gravitational waves from cosmological sources." Journal of Physics: Conference Series 610 (May 11, 2015): 012004. http://dx.doi.org/10.1088/1742-6596/610/1/012004.

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14

Corona, P., G. Ferrara, and M. Migliaccio. "Reverberating chambers as sources of stochastic electromagnetic fields." IEEE Transactions on Electromagnetic Compatibility 38, no. 3 (1996): 348–56. http://dx.doi.org/10.1109/15.536065.

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15

Wu, Bin, and Jijun Liu. "On the stability of recovering two sources and initial status in a stochastic hyperbolic-parabolic system." Inverse Problems 38, no. 2 (2022): 025010. http://dx.doi.org/10.1088/1361-6420/ac4426.

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Abstract Consider an inverse problem of determining two stochastic source functions and the initial status simultaneously in a stochastic thermoelastic system, which is constituted of two stochastic equations of different types, namely a parabolic equation and a hyperbolic equation. To establish the conditional stability for such a coupling system in terms of some suitable norms revealing the stochastic property of the governed system, we first establish two Carleman estimates with regular weight function and two large parameters for stochastic parabolic equation and stochastic hyperbolic equa

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16

Ellis, Justin, Fredrick Jenet, Xavier Siemens, and Maura McLaughlin. "Stochastic and continuous gravitational wave analysis pipelines for pulsar timing array data." Proceedings of the International Astronomical Union 8, S291 (2012): 178. http://dx.doi.org/10.1017/s1743921312023551.

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AbstractThe Nanohertz Observatory for Gravitational Waves (NANOGrav) collaboration aims to detect gravitational waves (GWs) through the precise timing of millisecond pulsars. GWs will come in the form of a stochastic background, continuous sources and burst sources. Here we will review recent progress on the development of data analysis pipelines aimed at the detection of a stochastic background as well as continuous sources. We will introduce the Optimal Statistic and F-Statistic methods that are used in the stochastic and continuous pipelines, respectively. Both pipelines are fully functiona

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17

Carter, Douglas R., and Frederick W. Cubbage. "Stochastic Frontier Estimation and Sources of Technical Efficiency in Southern Timber Harvesting." Forest Science 41, no. 3 (1995): 576–93. http://dx.doi.org/10.1093/forestscience/41.3.576.

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Abstract This research provides estimates of average industry and firm-specific technical efficiency using an econometric stochastic frontier production function for individual firms operating in the southern U.S. pulpwood harvesting industry in both 1979 and 1987. The stochastic frontier production function is capable of distinguishing deviations from the frontier due to uncontrollable stochastic elements, as well as provide a pure measure of technical efficiency. Results indicate that mean industry technical efficiency was nearly constant at 60% in both periods while frontier technical chang

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18

Fikal, Najib, Rajae Aboulaich, El Mahdi El Guarmah, and Nejib Zemzemi. "Propagation of two independent sources of uncertainty in the electrocardiography imaging inverse solution." Mathematical Modelling of Natural Phenomena 14, no. 2 (2019): 206. http://dx.doi.org/10.1051/mmnp/2018065.

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This study investigates the effects of the input parameter uncertainties (organ conductivities, boundary data, etc.) on the electrocardiography (ECG) imaging problem. These inputs are very important for the construction of the torso potential for the forward problem and for the non-invasive electrical potential on the heart surface in the case of the inverse problem. We propose a new stochastic formulation that allows us to combine both sources of errors. We formulate the forward and inverse stochastic problems by considering the input parameters as random fields and a stochastic optimal contr

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19

Wang, Haohua, Zhanjiang Yuan, Peijiang Liu, and Tianshou Zhou. "Division time-based amplifiers for stochastic gene expression." Molecular BioSystems 11, no. 9 (2015): 2417–28. http://dx.doi.org/10.1039/c5mb00391a.

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While cell-to-cell variability is a phenotypic consequence of gene expression noise, sources of this noise may be complex – apart from intrinsic sources such as the random birth/death of mRNA and stochastic switching between promoter states, there are also extrinsic sources of noise such as cell division where division times are either constant or random.

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20

CASSOL-SEEWALD, N. C., R. L. S. FARIAS, G. KREIN, and R. S. MARQUES DE CARVALHO. "NOISE AND ULTRAVIOLET DIVERGENCES IN SIMULATIONS OF GINZBURG–LANDAU–LANGEVIN TYPE OF EQUATIONS." International Journal of Modern Physics C 23, no. 08 (2012): 1240016. http://dx.doi.org/10.1142/s0129183112400165.

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The time evolution of an order parameter towards equilibrium can be described by nonlinear Ginzburg–Landau (GL) type of equations, also known as time-dependent nonlinear Schrödinger equations. Environmental effects of random nature are usually taken into account by noise sources, turning the GL equations into stochastic equations. Noise sources give rise to lattice-spacing dependence of the solutions of the stochastic equations. We present a systematic method to renormalize the equations on a spatial lattice to obtain lattice-spacing independent solutions. We illustrate the method in approxima

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21

Domański, Adam, Joanna Domańska, Katarzyna Filus, Jakub Szyguła, and Tadeusz Czachórski. "Self-Similar Markovian Sources." Applied Sciences 10, no. 11 (2020): 3727. http://dx.doi.org/10.3390/app10113727.

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Markov queueing models are a powerful tool to evaluate the performance of computer networks and have been used in telecommunication studies for over 100 years. To apply them to the evaluation of the modern Internet, we should not only adapt them to the contemporary network structures but also include a description of the complex stochastic patterns (self-similarity and long-range dependance) of transmitted flows. We examine the features of two Markov models of an almost self-similar process, keeping in mind the modeling of Internet traffic. We have found that the obtained results are comparabl

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22

Newby, Jay M. "Isolating intrinsic noise sources in a stochastic genetic switch." Physical Biology 9, no. 2 (2012): 026002. http://dx.doi.org/10.1088/1478-3975/9/2/026002.

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23

David, A. K. "Incorporation of large stochastic sources in the power system." IEE Proceedings C Generation, Transmission and Distribution 132, no. 4 (1985): 161. http://dx.doi.org/10.1049/ip-c.1985.0030.

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24

Klose, Alexander D. "Transport-theory-based stochastic image reconstruction of bioluminescent sources." Journal of the Optical Society of America A 24, no. 6 (2007): 1601. http://dx.doi.org/10.1364/josaa.24.001601.

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25

Kim, Kisik, and Emil Wolf. "A scalar-mode representation of stochastic, planar, electromagnetic sources." Optics Communications 261, no. 1 (2006): 19–22. http://dx.doi.org/10.1016/j.optcom.2005.12.005.

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26

van Foreest, Nicky D., Boudewijn R. Haverkort, Michel R. H. Mandjes, and Werner R. W. Scheinhardt. "Versatile stochastic models for networks with asymmetric TCP sources." Performance Evaluation 64, no. 6 (2007): 507–23. http://dx.doi.org/10.1016/j.peva.2006.07.001.

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27

Szczurek, Andrzej, Monika Maciejewska, Agnieszka Wyłomańska, Grzegorz Sikora, Michał Balcerek, and Marek Teuerle. "Discrimination of particulate matter emission sources using stochastic methods." Physica A: Statistical Mechanics and its Applications 463 (December 2016): 452–66. http://dx.doi.org/10.1016/j.physa.2016.06.071.

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28

Dupret, A., B. Granado, and P. Garda. "Scalable 2D arrays of noise sources for stochastic retina." Electronics Letters 33, no. 10 (1997): 849. http://dx.doi.org/10.1049/el:19970562.

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29

Mertsch, P. "Cosmic ray electrons and positrons from discrete stochastic sources." Journal of Cosmology and Astroparticle Physics 2011, no. 02 (2011): 031. http://dx.doi.org/10.1088/1475-7516/2011/02/031.

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30

SUN, L., and B. S. GREENBERG. "DYNAMIC RESPONSE OF LINEAR SYSTEMS TO MOVING STOCHASTIC SOURCES." Journal of Sound and Vibration 229, no. 4 (2000): 957–72. http://dx.doi.org/10.1006/jsvi.1999.2519.

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31

Ahmed, Alaa H., and Henrietta Tomán. "Stochastic Fusion Techniques for State Estimation." Computation 12, no. 10 (2024): 209. http://dx.doi.org/10.3390/computation12100209.

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The fusion process considers the boundary between correct and conflict records. It has been a fundamental component in ensuring the accuracy of many mathematical algorithms that utilize multiple input sources. Fusion techniques give priority and high weight to reliable and qualified sources since their information is most likely to be trustworthy. This study stochastically investigates the three most common fusion techniques: Kalman filtering, particle filtering and Bayesian probability (which is the basis of other techniques). The paper focuses on using fusion techniques in the context of sta

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32

Vanichpun, Sarut, and Armand M. Makowski. "WHEN ARE ON–OFF SOURCES SIS?: CONDITIONS AND APPLICATIONS." Probability in the Engineering and Informational Sciences 18, no. 4 (2004): 423–43. http://dx.doi.org/10.1017/s0269964804184015.

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Recent advances from the theory of multivariate stochastic orderings can be used to formalize the “folk theorem” that positive correlations lead to larger buffer levels at a discrete-time infinite capacity multiplexer queue. In particular, it is known that if the input traffic is larger than its independent version in the supermodular (sm) ordering, then their corresponding buffer contents are similarly ordered in the increasing convex (icx) ordering.A sufficient condition for the aforementioned sm comparison is the stochastic increasingness in sequence (SIS) property of the input traffic. In

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33

Hattori, Motofumi, Masahiko Tsuji, Satoshi Tadokoro, Toshi Takamori, and Kazuhito Yamada. "An Analysis and Generation of Bunraku Puppet's Motions Based on Linear Structure of Functional Factors, Emotional Factors and Stochastic Fluctuations for Generation of Humanoid Robots' Actions with Fertile Emotions." Journal of Robotics and Mechatronics 11, no. 5 (1999): 393–98. http://dx.doi.org/10.20965/jrm.1999.p0393.

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Human robots must have actions with fertile emotions, in order to cooperate with human being. To clarify ""what is the emotional factor of actions"", the authors analyze the actions of a Bunraku puppet. The observed action time series are modeled by a stochastic time evolutionequations (KM2O-Langevin equations) with exogenoussources which represent the sources of functional factors, emotional factors and stochastic fluctuation factors. The estimation method for KM2O-Langevin equations with exogenous sources is established. This method is verified by a numerical simulation.

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34

Kovtun, Svitlana, Oleksandr Ponomarenko, and Oleg Nazarenko. "Quality of the information flow management at stochastic energy consumption conditions." System Research in Energy 2023, no. 3 (2023): 78–84. http://dx.doi.org/10.15407/srenergy2023.03.078.

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Modern energy systems are rapidly changing and becoming increasingly complex. This process is facilitated by the growing demand for distributed energy resources, renewable energy sources, and distributed generation. This makes the energy system highly stochastic. An integral part of the concept of smart grids is the production of energy from distributed energy sources. Modernization of the energy network with the help of intelligent technologies allows us to fully take into account the peculiarities of energy consumption. The smart grid paradigm envisions flexible energy demand and storage to

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35

Koole, Ger, and Zhen Liu. "Stochastic Bounds for Queueing Systems with Multiple On–Off Sources." Probability in the Engineering and Informational Sciences 12, no. 1 (1998): 25–48. http://dx.doi.org/10.1017/s0269964800005040.

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Consider a queueing system where the input traffic consists of background traffic, modeled by a Markov Arrival Process, and foreground traffic modeled by N ≥ 1 homogeneous on–off sources. The queueing system has an increasing and concave service rate, which includes as a particular case multiserver queueing systems. Both the infinite-capacity and the finite-capacity buffer cases are analyzed. We show that the queue length in the infinite-capacity buffer system (respectively, the number of losses in the finite-capacity buffer system) is larger in the increasing convex order sense (respectively,

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36

Carvalho, Jonas Da Costa, Gervásio Annes Degrazia, Domenico Anfossi, Cláudia Rejane Jacondino De Campos, Débora Regina Roberti, and Américo Sansigolo Kerr. "Lagrangian stochastic dispersion modelling for the simulation of the release of contaminants from tall and low sources." Meteorologische Zeitschrift 11, no. 2 (2002): 89–97. http://dx.doi.org/10.1127/0941-2948/2002/0011-0089.

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37

Dumbrava, V., G.C. Lazaroiu, G. Bazacliu, and M. Teliceanu. "Stochastic Optimization of Power System Operation in Presence of Renewable Energy Sources." Problemele Energeticii Regionale 3(32) (December 15, 2016): 85–90. https://doi.org/10.5281/zenodo.1207931.

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The liberalization process of the energy market structure determined significant changes in the electric utility industry, from both generating and transmission perspectives, and new generation technologies emerged, deeply influencing the industry profile. Nowadays, based on the governmental incentives and free access to the power systems, the share of renewable energy sources in the bulk power system generation is increasing. With respect to the classical fuel-based sources, the renewable energy sources (like photovoltaic and wind turbines) have an intermittent character determined by the met

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38

Takahashi, Koji, and Shogo Inagaki. "Post-Collapse Evolution of Globular Clusters with Stochastic Energy Sources." Publications of the Astronomical Society of Japan 43, no. 4 (1991): 589–606. https://doi.org/10.1093/pasj/43.4.589.

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Abstract The effects of the stochasticity of binary activity on the post-collapse evolution of globular clusters are investigated by directly integrating the Fokker-Planck equation. By comparing the present results of computations with those of continuous energy sources, it is found that the stochasticity of binary activity makes core evolution more unstable. For example, a cluster with N = 10000 stars experiences chaotic gravothermal oscillations in the case of stochastic energy sources, whereas one with continuous energy sources exhibits regular oscillations. The stochasticity, however, does

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39

Fonseca, António Jorge Filipe. "Two Informational Complexity Measures in Social Networks and Agent Communities." International Journal of Agent Technologies and Systems 1, no. 4 (2009): 49–57. http://dx.doi.org/10.4018/jats.2009071004.

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Several informational complexity measures rely on the notion of stochastic process in order to extract hidden structural properties behind the apparent randomness of information sources. Following an equivalence approach between dynamic relation evolution within a social network and a generic stochastic process two dynamic measures of network complexity are proposed.

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40

Bordini, Lorenzo, and Giuseppe Taino. "[The stochastic effects of ionising radiation]." Giornale Italiano di Medicina del Lavoro ed Ergonomia 39, no. 2 (2017): 116–23. https://doi.org/10.4081/gimle.615.

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Stochastic effects induced by exposure to ionizing radiation rapresent a relevance radioprotection aspect. Actually most of the information about radiation-induced oncogenic risk arise from the follow-up of the atomic bombs survivors (Life Span Study, LSS); at this information sources have been added over the last decades also data derived from medical, occupational and environmental studies conducted in various parts of the world and their contribution about number of cases and duration of follow-up period is of great relevance.These sources of information, in fact, provide important data rel

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41

Junlakarn, Siripha, Radhanon Diewvilai, and Kulyos Audomvongseree. "Stochastic Modeling of Renewable Energy Sources for Capacity Credit Evaluation." Energies 15, no. 14 (2022): 5103. http://dx.doi.org/10.3390/en15145103.

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In power system planning, the growth of renewable energy generation leads to several challenges including system reliability due to its intermittency and uncertainty. To quantify the relatively reliable capacity of this generation, capacity credit is usually adopted for long-term power system planning. This paper proposes an evaluation of the capacity credit of renewable energy generation using stochastic models for resource availability. Six renewable energy generation types including wind, solar PV, small hydro, biomass, biogas, and waste were considered. The proposed models are based on the

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42

Ward, Lawrence M., Shannon E. MacLean, and Aaron Kirschner. "Stochastic Resonance Modulates Neural Synchronization within and between Cortical Sources." PLoS ONE 5, no. 12 (2010): e14371. http://dx.doi.org/10.1371/journal.pone.0014371.

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43

Logothetis, A., and V. Krishnamurthy. "An interval-amplitude algorithm for deinterleaving stochastic pulse train sources." IEEE Transactions on Signal Processing 46, no. 5 (1998): 1344–50. http://dx.doi.org/10.1109/78.668796.

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44

Natarajan, B., K. Konstantinides, and C. Herley. "Occam filters for stochastic sources with application to digital images." IEEE Transactions on Signal Processing 46, no. 5 (1998): 1434–38. http://dx.doi.org/10.1109/78.668806.

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45

Coffman, E. G., B. M. Igelnik, and Y. A. Kogan. "Controlled stochastic model of a communication system with multiple sources." IEEE Transactions on Information Theory 37, no. 5 (1991): 1379–87. http://dx.doi.org/10.1109/18.133255.

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46

Stanković, Zoran, Nebojsa Dončov, Ivan Milovanović, and Bratislav Milovanović. "DoA estimation of highly correlated stochastic sources using neural model." Electromagnetics 38, no. 8 (2018): 500–516. http://dx.doi.org/10.1080/02726343.2018.1519161.

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47

Tessone, Claudio J., Horacio S. Wio, and Peter Hänggi. "Stochastic resonance driven by time-modulated correlated white noise sources." Physical Review E 62, no. 4 (2000): 4623–32. http://dx.doi.org/10.1103/physreve.62.4623.

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48

Goda, Katsuichiro. "Time-dependent probabilistic tsunami hazard analysis using stochastic rupture sources." Stochastic Environmental Research and Risk Assessment 33, no. 2 (2018): 341–58. http://dx.doi.org/10.1007/s00477-018-1634-x.

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49

Anastasopoulos, Markos, Anna Tzanakaki, and Dimitra Simeonidou. "Stochastic Energy Efficient Cloud Service Provisioning Deploying Renewable Energy Sources." IEEE Journal on Selected Areas in Communications 34, no. 12 (2016): 3927–40. http://dx.doi.org/10.1109/jsac.2016.2600061.

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50

Hyde, Milo W. "Stochastic complex transmittance screens for synthesizing general partially coherent sources." Journal of the Optical Society of America A 37, no. 2 (2020): 257. http://dx.doi.org/10.1364/josaa.381772.

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