Relevant bibliographies by topics / Random processes

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
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Academic literature on the topic 'Random processes'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Random processes"

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Poliarus, Oleksandr, Andrii Lebedynskyi, Yevhenii Chepusenko, and Nina Lyubymova. "Visualization method for multidimentional random processes." Measuring Equipment and Metrology 84, no. 1 (2023): 5–10. http://dx.doi.org/10.23939/istcmtm2023.01.005.

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The article proposes a method for visualizing multidimensional random process realizations using the example of the concentrations of harmful gases emitted into the atmosphere from a thermal power plant. The method is based on the transformation of gas concentration values in one point of multidimensional space at the same time into a two-dimensional curve, which is described by the sum of products of normalized concentrations by orthogonal Legendre functions of the corresponding order. The combination of such curves on a two-dimensional plane at discrete times creates a characteristic image t
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Alexander, Kenneth S., and Steven A. Kalikow. "Random Stationary Processes." Annals of Probability 20, no. 3 (1992): 1174–98. http://dx.doi.org/10.1214/aop/1176989685.

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ROBALEWSKA, H. D., and N. C. WORMALD. "Random Star Processes." Combinatorics, Probability and Computing 9, no. 1 (2000): 33–43. http://dx.doi.org/10.1017/s096354839900406x.

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Bandt, Christoph. "Ordinal Random Processes." Entropy 27, no. 6 (2025): 610. https://doi.org/10.3390/e27060610.

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Ordinal patterns have proven to be a valuable tool in many fields. Here, we address the need for theoretical models. A paradigmatic example shows that a model for frequencies of ordinal patterns can be determined without any numerical values. We specify the important concept of stationary order and the fundamental problems to be solved in order to establish a genuine statistical methodology for ordinal time series.
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Aitken, G. J. M. "Illustrating Random Processes with Random Phase Modulation." International Journal of Electrical Engineering & Education 23, no. 2 (1986): 151–58. http://dx.doi.org/10.1177/002072098602300209.

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Randomly phase-modulated cosines are a source of examples for illustrating the topics of variance, autocorrelation, conditional probability and filtering. Mathematical manipulations are neither difficult nor tedious despite the non-linear relationship between measured quantities and the phase noise. The basic mathematical framework is presented in the context of examples which include synchronous detection in the presence of phase perturbations.
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Lyashenko, N. N. "Graphs of Random Processes as Random Sets." Theory of Probability & Its Applications 31, no. 1 (1987): 72–80. http://dx.doi.org/10.1137/1131006.

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Applebaum, David, Geoffrey Grimmett, David Stirzaker, Marek Capiński, Thomas Zastawniak, and Marek Capinski. "Probability and Random Processes." Mathematical Gazette 86, no. 505 (2002): 185. http://dx.doi.org/10.2307/3621637.

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Foutz, Robert V., G. R. Grimmett, and D. R. Stirzaker. "Probability and Random Processes." Journal of the American Statistical Association 88, no. 424 (1993): 1475. http://dx.doi.org/10.2307/2291308.

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Stoyanov, Jordan. "Probability and Random Processes." Journal of the Royal Statistical Society: Series A (Statistics in Society) 170, no. 4 (2007): 1183–84. http://dx.doi.org/10.1111/j.1467-985x.2007.00506_12.x.

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Meyer, Mary C., and Donald G. Childers. "Probability and Random Processes." Journal of the American Statistical Association 94, no. 447 (1999): 988. http://dx.doi.org/10.2307/2670024.

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Dissertations / Theses on the topic "Random processes"

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Makai, Tamas. "Random graph processes." Thesis, Royal Holloway, University of London, 2012. http://repository.royalholloway.ac.uk/items/b24b89af-3fc1-4d2f-a673-64483a3bc2f2/8/.

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This thesis deals with random graph processes. More precisely it deals with two random graph processes which create H -free graphs. The first of these processes is the random H-elimination process which starts from the complete graph and in every step removes an edge uniformly at random from the set of edges which are found in a copy of H. The second is the H-free random graph process which starts from the empty graph and in every step an edge chosen uniformly at random from the set of edges which when added to the graph would not create a copy of H is inserted. We consider these graph process
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Kang, Mihyun. "Random planar structures and random graph processes." Doctoral thesis, [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=985516585.

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Zielen, Frank H. "Asymmetric random average processes." [S.l.] : [s.n.], 2002. http://deposit.ddb.de/cgi-bin/dokserv?idn=965270475.

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Timar, Adam. "Group-invariant random processes." [Bloomington, Ind.] : Indiana University, 2006. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:3204537.

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Thesis (Ph.D.)--Indiana University, Dept. of Mathematics, 2006.<br>Source: Dissertation Abstracts International, Volume: 67-01, Section: B, page: 0308. Adviser: Russell Lyons. "Title from dissertation home page (viewed Feb. 9, 2007)."
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Ortgiese, Marcel. "Stochastic processes in random environment." Thesis, University of Bath, 2009. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.507234.

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We are interested in two probabilistic models of a process interacting with a random environment. Firstly, we consider the model of directed polymers in random environment. In this case, a polymer, represented as the path of a simple random walk on a lattice, interacts with an environment given by a collection of time-dependent random variables associated to the vertices. Under certain conditions, the system undergoes a phase transition from an entropy-dominated regime at high temperatures, to a localised regime at low temperatures. Our main result shows that at high temperatures, even though
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Warnke, Lutz. "Random graph processes with dependencies." Thesis, University of Oxford, 2012. http://ora.ox.ac.uk/objects/uuid:71b48e5f-a192-4684-a864-ea9059a25d74.

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Random graph processes are basic mathematical models for large-scale networks evolving over time. Their systematic study was pioneered by Erdös and Rényi around 1960, and one key feature of many 'classical' models is that the edges appear independently. While this makes them amenable to a rigorous analysis, it is desirable, both mathematically and in terms of applications, to understand more complicated situations. In this thesis the main goal is to improve our rigorous understanding of evolving random graphs with significant dependencies. The first model we consider is known as an Achlioptas
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Ding, Xinhong Carleton University Dissertation Mathematics. "Diffusion processes with random interactions." Ottawa, 1992.

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Seierstad, Taral Guldahl. "The phase transition in random graphs and random graph processes." Doctoral thesis, [S.l.] : [s.n.], 2007. http://deposit.ddb.de/cgi-bin/dokserv?idn=985760044.

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Hu, Yilei. "Essays on random processes with reinforcement." Thesis, University of Oxford, 2010. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.669991.

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Figwer, Jarosław. "Synthesis and simulation of random processes." Praca habilitacyjna, Wydawnictwo Politechniki Śląskiej, 1999. https://delibra.bg.polsl.pl/dlibra/docmetadata?showContent=true&id=8070.

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Books on the topic "Random processes"

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Grimmett, Geoffrey. Probability and random processes. 3rd ed. Oxford University Press, 2004.

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Skorokhod, A. V. Random processes with independent increments. Kluwer Academic Publishers, 1991.

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David, Stirzaker, ed. Probability and random processes. 3rd ed. Oxford University Press, 2001.

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David, Stirzaker, ed. Probability and random processes. 2nd ed. Clarendon Press, 1992.

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David, Stirzaker, ed. Probability and random processes. Clarendon Press, 1992.

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Harnad, John, ed. Random Matrices, Random Processes and Integrable Systems. Springer New York, 2011. http://dx.doi.org/10.1007/978-1-4419-9514-8.

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Grami, Ali. Probability, Random Variables, Statistics, and Random Processes. John Wiley & Sons, Inc., 2019. http://dx.doi.org/10.1002/9781119300847.

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Hsu, Hwei P. Schaum's outlines: Probability, random variables & random processes. 2nd ed. McGraw-Hill, 2011.

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Leszek, Gawarecki, ed. Stochastic analysis for Gaussian random processes and fields: With applications. CRC Press, Taylor & Francis Group, 2016.

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Krishnan, Venkatarama. Probability and Random Processes. John Wiley & Sons, Inc., 2005. http://dx.doi.org/10.1002/0471998303.

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Book chapters on the topic "Random processes"

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Wang, Yingguang. "Random Processes." In Random Vibrations. CRC Press, 2024. https://doi.org/10.1201/9781003431503-3.

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Harwit, Martin. "Random Processes." In Astrophysical Concepts. Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4757-2019-8_4.

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Carlton, Matthew A., and Jay L. Devore. "Random Processes." In Probability with Applications in Engineering, Science, and Technology. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52401-6_7.

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Gebali, Fayez. "Random Processes." In Analysis of Computer and Communication Networks. Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74437-7_2.

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Harwit, Martin. "Random Processes." In Astrophysical Concepts. Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-2928-3_4.

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Carlton, Matthew A., and Jay L. Devore. "Random Processes." In Probability with Applications in Engineering, Science, and Technology. Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0395-5_7.

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Chonavel, Thierry. "Random Processes." In Statistical Signal Processing. Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0139-0_2.

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Preumont, André. "Random Processes." In Random Vibration and Spectral Analysis. Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-017-2840-9_3.

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Rozanov, Yu A. "Random Processes." In Probability Theory, Random Processes and Mathematical Statistics. Springer Netherlands, 1995. http://dx.doi.org/10.1007/978-94-011-0449-4_2.

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Cipra, Tomas. "Random Processes." In Time Series in Economics and Finance. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-46347-2_2.

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Conference papers on the topic "Random processes"

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Vélez, Ricardo, and Tomás Prieto-Rumeau. "Random Assignment Processes." In Annual International Conference on Operations Research and Statistics. Global Science & Technology Forum (GSTF), 2012. http://dx.doi.org/10.5176/2251-1938_ors46.

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Wilkowski, D., R. Kaiser, G. Labeyrie, et al. "Light transport in cold atoms: dephasing processes." In Photonic Metamaterials: From Random to Periodic. OSA, 2007. http://dx.doi.org/10.1364/meta.2007.thc4.

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Cohen, Leon. "Classical and Quantum Random Processes." In INFORMATION OPTICS: 5th International Workshop on Information Optics (WIO'06). AIP, 2006. http://dx.doi.org/10.1063/1.2361208.

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Treviño, George, Jay Hardin, Bruce Douglas, and Edgar Andreas. "Current Topics in Nonstationary Analysis." In Second Workshop on Nonstationary Random Processes and Their Applications. WORLD SCIENTIFIC, 1996. http://dx.doi.org/10.1142/9789812833099.

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Si, Si. "Gaussian processes and Gaussian random fields." In Proceedings of the Second International Conference. WORLD SCIENTIFIC, 2000. http://dx.doi.org/10.1142/9789812792761_0015.

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Chernoyarov, Oleg. "Digital simulators of the random processes." In The 33rd European Modeling & Simulation Symposium. CAL-TEK srl, 2021. http://dx.doi.org/10.46354/i3m.2021.emss.007.

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Thomson, D. J. "Reconstruction of unequally-sampled random processes." In 2005 Microwave Electronics: Measurements, Identification, Applications. IEEE, 2005. http://dx.doi.org/10.1109/ssp.2005.1628696.

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Galleani, Lorenzo, Leon Cohen, and Bruce Suter. "Locally Stationary Noise and Random Processes." In INFORMATION OPTICS: 5th International Workshop on Information Optics (WIO'06). AIP, 2006. http://dx.doi.org/10.1063/1.2361257.

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Azzi, S., Y. Huang, B. Sudret, and J. Wiart. "Random Processes Metamodeling Applied to Dosimetry." In 2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC). IEEE, 2018. http://dx.doi.org/10.23919/ursi-at-rasc.2018.8471520.

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Li, Yanbin, Sameer B. Mulani, Rakesh K. Kapania, Shaoqing Wu, and Qingguo Fei. "Non-Stationary Random Vibration Analysis Using Multi-Correlated Random Processes Excitations." In 57th AIAA/ASCE/AHS/ASC Structures, Structural Dynamics, and Materials Conference. American Institute of Aeronautics and Astronautics, 2016. http://dx.doi.org/10.2514/6.2016-2173.

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Reports on the topic "Random processes"

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Freidlin, Mark. PDE's, Random Processes and Fields: Asymptotic Problems. Defense Technical Information Center, 1995. http://dx.doi.org/10.21236/ada304572.

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Leadbetter, M. R. On the Exeedance Random Measures for Stationary Processes. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada192838.

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Voychishin, K. S., and Ya P. Dragan. Elimination Of Rhythm For Periodically Correlated Random Processes. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada261061.

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Young, Richard M. Modeling Random Walk Processes In Human Concept Learning. Defense Technical Information Center, 2006. http://dx.doi.org/10.21236/ada462700.

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Michels, James H. Synthesis of Multichannel Autoregressive Random Processes and Ergodicity Considerations. Defense Technical Information Center, 1990. http://dx.doi.org/10.21236/ada226493.

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Slavtchova-Bojkova, Maroussia N., Ollivier Hyrien, and Nikolay M. Yanev. Poisson Random Measures and Noncritical Multitype Markov Branching Processes. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, 2021. http://dx.doi.org/10.7546/crabs.2021.05.03.

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Lunsford, Kurt G., and Kenneth D. West. Random Walk Forecasts of Stationary Processes Have Low Bias. Federal Reserve Bank of Cleveland, 2023. http://dx.doi.org/10.26509/frbc-wp-202318.

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We study the use of a zero mean first difference model to forecast the level of a scalar time series that is stationary in levels. Let bias be the average value of a series of forecast errors. Then the bias of forecasts from a misspecified ARMA model for the first difference of the series will tend to be smaller in magnitude than the bias of forecasts from a correctly specified model for the level of the series. Formally, let P be the number of forecasts. Then the bias from the first difference model has expectation zero and a variance that is O(1/P²), while the variance of the bias from the l
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Alfano, R. R., F. Liu, Y. Guo, C. H. Liu, and J. Ying. Optical Amplification and Nonlinear Optical Processes in Random Scattering Media. Defense Technical Information Center, 2000. http://dx.doi.org/10.21236/ada377025.

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Getoor, R. K., and Joseph Glover. Constructing Markov Processes with Random Times of Birth and Death,. Defense Technical Information Center, 1986. http://dx.doi.org/10.21236/ada171856.

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Michels, James H. Correlation Function Estimator Performance in Non-Gaussian Spherically Invariant Random Processes. Defense Technical Information Center, 1993. http://dx.doi.org/10.21236/ada273498.

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