Academic literature on the topic 'Processi random'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Processi random.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Processi random"
Kouznetsov, Dimitrii, and Valerii Voitsekhovich. "Die Methode der zufälligen Wellenvektoren zur Simulation von korrelierten Zufallsprozessen." Meteorologische Zeitschrift 7, no. 5 (November 2, 1998): 230–36. http://dx.doi.org/10.1127/metz/7/1998/230.
Full textFRYZ, Mykhailo, and Bogdana MLYNKO. "DISCRETE-TIME CONDITIONAL LINEAR RANDOM PROCESSES AND THEIR PROPERTIES." Herald of Khmelnytskyi National University. Technical sciences 309, no. 3 (May 26, 2022): 7–12. http://dx.doi.org/10.31891/2307-5732-2022-309-3-7-12.
Full textXu, Hongzhi, Chunping Li, Li Li, and Hongyu Shi. "Accelerating the Training Process of Support Vector Machines by Random Partition." International Journal of Computer Theory and Engineering 7, no. 1 (February 2014): 29–33. http://dx.doi.org/10.7763/ijcte.2015.v7.925.
Full textBaddeley, A. J., and L. M. Cruz-Orive. "The Rao–Blackwell theorem in stereology and some counterexamples." Advances in Applied Probability 27, no. 01 (March 1995): 2–19. http://dx.doi.org/10.1017/s0001867800046188.
Full textDuong, Dam Ton, and Hao Ngoc Duong. "ITÔ – HERMITE RANDOM PROCESS." Science and Technology Development Journal 13, no. 3 (September 30, 2010): 13–18. http://dx.doi.org/10.32508/stdj.v13i3.2149.
Full textChung, Jaeyoung, Dohan Kim, and Eun Gu Lee. "Stationary hyperfunctional random process." Complex Variables and Elliptic Equations 59, no. 11 (March 14, 2013): 1547–58. http://dx.doi.org/10.1080/17476933.2012.757309.
Full textKorándi, Dániel, Yuval Peled, and Benny Sudakov. "A Random Triadic Process." SIAM Journal on Discrete Mathematics 30, no. 1 (January 2016): 1–19. http://dx.doi.org/10.1137/15m1012487.
Full textSchulman, Leonard J. "A random stacking process." Discrete Mathematics 257, no. 2-3 (November 2002): 541–47. http://dx.doi.org/10.1016/s0012-365x(02)00512-5.
Full textSibuya, Masaaki. "A random clustering process." Annals of the Institute of Statistical Mathematics 45, no. 3 (1993): 459–65. http://dx.doi.org/10.1007/bf00773348.
Full textWelsh, D. J. A. "The random cluster process." Discrete Mathematics 136, no. 1-3 (December 1994): 373–90. http://dx.doi.org/10.1016/0012-365x(94)00120-8.
Full textDissertations / Theses on the topic "Processi random"
Dionigi, Pierfrancesco. "A random matrix theory approach to complex networks." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019. http://amslaurea.unibo.it/18513/.
Full textSiena, Martina. "Caratterizzazione della permeabilità in mezzi porosi sintetici e naturali." Doctoral thesis, Università degli studi di Trieste, 2013. http://hdl.handle.net/10077/8661.
Full textLa presente tesi ha come principale obiettivo lo studio della variabilità di proprietà idrologiche in mezzi porosi, con particolare attenzione alla permeabilità. A tal fine, ci si avvale di un approccio che combina l'analisi di proprietà statistiche e di scaling applicata a dataset di permeabilità, con lo studio di risultati numerici di simulazioni di flusso alla microscala in mezzi porosi. Con la prima analisi è possibile caratterizzare variazioni di permeabilità alla scala di misura (tipicamente dell'ordine del centimetro), mentre la seconda analisi dà una descrizione dell'eterogeneità di permeabilità ad una scala inferiore (nell'ordine del millimetro), ottenuta risolvendo processi fisici alla scala dei pori e derivando le quantità integrali di interesse. L'analisi statistica e di scaling, effettuata sia su distribuzioni di permeabilità sintetiche, sia su dataset raccolti su campioni reali, avvalora la validità dei modelli truncated fractional Brownian motion (tfBm) e truncated fractional Gaussian noise (tfGn), o di processi random sub-Gaussiani ad essi subordinati, per l'interpretazione della variabilità di proprietà idrologiche. Soluzioni numeriche di campi di flusso (i.e. velocità e pressione) alla scala dei pori sono ottenute sia per campioni sintetici, sia per campioni reali, la cui geometria è ricostruita mediante micro-tomografia a raggi X. Diverse metodologie di applicazione delle condizioni al contorno in corrispondenza dell'interfaccia liquido-solido forniscono risultati qualitativamente simili sia in termini di quantità microscopiche, sia in termini di quantità medie.
The work is aimed at providing some insights on the variability of hydrological properties in porous media, focusing in particular on permeability. We consider an approach which combines scaling and statistical analyses of air-permeability datasets with pore-scale numerical simulations of flow through porous media. The former investigation allows to characterize permeability heterogeneity at the centimeter observation scale; the latter provides a description of heterogeneity on a millimeter scale by resolving physical processes occurring at the microscopic scale and deriving up-scaled quantities. Scaling and statistical analyses performed on synthetic permeability distributions as well as on datasets collected on real media support the identification of truncated fractional Brownian motion (tfBm) or truncated fractional Gaussian noise (tfGn) and of sub-Gaussian random processes subordinated to tfBm (or tfGn) as viable models for the interpretation of hydrological properties variability. Pore-scale numerical solutions of flow (i.e., in terms of velocity and pressure distributions) are performed on both randomly generated samples and real porous media reconstructed via X-ray Micro-Tomography. Different approaches for the enforcement of boundary conditions at the fluid-solid interface provide qualitatively similar results in terms of both microscopic and averaged quantities.
XXV Ciclo
1984
Hannigan, Patrick. "Random polynomials." Thesis, University of Ulster, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.263248.
Full textLi, Zheng. "Approximation to random process by wavelet basis." View abstract/electronic edition; access limited to Brown University users, 2008. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3318378.
Full textBuckley, Stephen Philip. "Problems in random walks in random environments." Thesis, University of Oxford, 2011. http://ora.ox.ac.uk/objects/uuid:06a12be2-b831-4c2a-87b1-f0abccfb9b8b.
Full textAuret, Lidia. "Process monitoring and fault diagnosis using random forests." Thesis, Stellenbosch : University of Stellenbosch, 2010. http://hdl.handle.net/10019.1/5360.
Full textDissertation presented for the Degree of DOCTOR OF PHILOSOPHY (Extractive Metallurgical Engineering) in the Department of Process Engineering at the University of Stellenbosch
ENGLISH ABSTRACT: Fault diagnosis is an important component of process monitoring, relevant in the greater context of developing safer, cleaner and more cost efficient processes. Data-driven unsupervised (or feature extractive) approaches to fault diagnosis exploit the many measurements available on modern plants. Certain current unsupervised approaches are hampered by their linearity assumptions, motivating the investigation of nonlinear methods. The diversity of data structures also motivates the investigation of novel feature extraction methodologies in process monitoring. Random forests are recently proposed statistical inference tools, deriving their predictive accuracy from the nonlinear nature of their constituent decision tree members and the power of ensembles. Random forest committees provide more than just predictions; model information on data proximities can be exploited to provide random forest features. Variable importance measures show which variables are closely associated with a chosen response variable, while partial dependencies indicate the relation of important variables to said response variable. The purpose of this study was therefore to investigate the feasibility of a new unsupervised method based on random forests as a potentially viable contender in the process monitoring statistical tool family. The hypothesis investigated was that unsupervised process monitoring and fault diagnosis can be improved by using features extracted from data with random forests, with further interpretation of fault conditions aided by random forest tools. The experimental results presented in this work support this hypothesis. An initial study was performed to assess the quality of random forest features. Random forest features were shown to be generally difficult to interpret in terms of geometry present in the original variable space. Random forest mapping and demapping models were shown to be very accurate on training data, and to extrapolate weakly to unseen data that do not fall within regions populated by training data. Random forest feature extraction was applied to unsupervised fault diagnosis for process data, and compared to linear and nonlinear methods. Random forest results were comparable to existing techniques, with the majority of random forest detections due to variable reconstruction errors. Further investigation revealed that the residual detection success of random forests originates from the constrained responses and poor generalization artifacts of decision trees. Random forest variable importance measures and partial dependencies were incorporated in a visualization tool to allow for the interpretation of fault conditions. A dynamic change point detection application with random forests proved more successful than an existing principal component analysis-based approach, with the success of the random forest method again residing in reconstruction errors. The addition of random forest fault diagnosis and change point detection algorithms to a suite of abnormal event detection techniques is recommended. The distance-to-model diagnostic based on random forest mapping and demapping proved successful in this work, and the theoretical understanding gained supports the application of this method to further data sets.
AFRIKAANSE OPSOMMING: Foutdiagnose is ’n belangrike komponent van prosesmonitering, en is relevant binne die groter konteks van die ontwikkeling van veiliger, skoner en meer koste-effektiewe prosesse. Data-gedrewe toesigvrye of kenmerkekstraksie-benaderings tot foutdiagnose benut die vele metings wat op moderne prosesaanlegte beskikbaar is. Party van die huidige toesigvrye benaderings word deur aannames rakende liniariteit belemmer, wat as motivering dien om nie-liniêre metodes te ondersoek. Die diversiteit van datastrukture is ook verdere motivering vir ondersoek na nuwe kenmerkekstraksiemetodes in prosesmonitering. Lukrake-woude is ’n nuwe statistiese inferensie-tegniek, waarvan die akkuraatheid toegeskryf kan word aan die nie-liniêre aard van besluitnemingsboomlede en die bekwaamheid van ensembles. Lukrake-woudkomitees verskaf meer as net voorspellings; modelinligting oor datapuntnabyheid kan benut word om lukrakewoudkenmerke te verskaf. Metingbelangrikheidsaanduiers wys watter metings in ’n noue verhouding met ’n gekose uitsetveranderlike verkeer, terwyl parsiële afhanklikhede aandui wat die verhouding van ’n belangrike meting tot die gekose uitsetveranderlike is. Die doel van hierdie studie was dus om die uitvoerbaarheid van ’n nuwe toesigvrye metode vir prosesmonitering gebaseer op lukrake-woude te ondersoek. Die ondersoekte hipotese lui: toesigvrye prosesmonitering en foutdiagnose kan verbeter word deur kenmerke te gebruik wat met lukrake-woude geëkstraheer is, waar die verdere interpretasie van foutkondisies deur addisionele lukrake-woude-tegnieke bygestaan word. Eksperimentele resultate wat in hierdie werkstuk voorgelê is, ondersteun hierdie hipotese. ’n Intreestudie is gedoen om die gehalte van lukrake-woudkenmerke te assesseer. Daar is bevind dat dit moeilik is om lukrake-woudkenmerke in terme van die geometrie van die oorspronklike metingspasie te interpreteer. Verder is daar bevind dat lukrake-woudkartering en -dekartering baie akkuraat is vir opleidingsdata, maar dat dit swak ekstrapolasie-eienskappe toon vir ongesiene data wat in gebiede buite dié van die opleidingsdata val. Lukrake-woudkenmerkekstraksie is in toesigvrye-foutdiagnose vir gestadigde-toestandprosesse toegepas, en is met liniêre en nie-liniêre metodes vergelyk. Resultate met lukrake-woude is vergelykbaar met dié van bestaande metodes, en die meerderheid lukrake-woudopsporings is aan metingrekonstruksiefoute toe te skryf. Verdere ondersoek het getoon dat die sukses van res-opsporing op die beperkte uitsetwaardes en swak veralgemenende eienskappe van besluitnemingsbome berus. Lukrake-woude-metingbelangrikheidsaanduiers en parsiële afhanklikhede is ingelyf in ’n visualiseringstegniek wat vir die interpretasie van foutkondisies voorsiening maak. ’n Dinamiese aanwending van veranderingspuntopsporing met lukrake-woude is as meer suksesvol bewys as ’n bestaande metode gebaseer op hoofkomponentanalise. Die sukses van die lukrake-woudmetode is weereens aan rekonstruksie-reswaardes toe te skryf. ’n Voorstel wat na aanleiding van hierde studie gemaak is, is dat die lukrake-woudveranderingspunt- en foutopsporingsmetodes by ’n soortgelyke stel metodes gevoeg kan word. Daar is in hierdie werk bevind dat die afstand-vanaf-modeldiagnostiek gebaseer op lukrake-woudkartering en -dekartering suksesvol is vir foutopsporing. Die teoretiese begrippe wat ontsluier is, ondersteun die toepassing van hierdie metodes op verdere datastelle.
Kandler, Anne, Matthias Richter, Scheidt Jürgen vom, Hans-Jörg Starkloff, and Ralf Wunderlich. "Moving-Average approximations of random epsilon-correlated processes." Universitätsbibliothek Chemnitz, 2004. http://nbn-resolving.de/urn:nbn:de:swb:ch1-200401266.
Full textIuliano, Antonella. "Analysis of a birth and death process with alternating rates and of a telegraph process with underlying random walk." Doctoral thesis, Universita degli studi di Salerno, 2012. http://hdl.handle.net/10556/311.
Full textMy thesis for the Doctoral Programme in Mathematics (November 1, 2008 - October 31, 2011) at University of Salerno, Italy, has been oriented to the analysis of two stochastic models, with particular emphasis on the de- termination of their probability laws and related properties. The discussion of the doctoral dissertation will be given in 20 March 2012. The first part of the thesis is devoted to the analysis of a birth and death process with alternating rates. We recall that an extensive survey on birth- death processes (BDP) has been provided by Parthasarathy and Lenin [3]. In this work the authors adopt standard methods of analysis (such as power series technique and Laplace transforms) to find explicit expressions for the transient and stationary distributions of BDPs and provide applications of such results to specific fields (communication systems, chemical and biolog- ical models). In particular, in Section 9 they use BDPs to describe the time changes in the concentrations of the components of a chemical reaction and discuss the role of BDPs in the study of diatomic molecular chains. More- over, the paper by StockMayer et al. [4] gives an example of application of stochastic processes in the study of chain molecular diffusion. In this work a molecule is modeled as a freely-joined chain of two regularly alternating kinds of atoms. All bonds have the same length but the two kinds of atoms have alternating jump rates, i.e. the forward and backward jump rates for even labeled beads are α and β, respectively, and these rates are reversed for odd labeled beads. The authors obtain the exact timedependent aver- age length of bond vectors. Inspired by this works, Conolly [1] studied an infinitely long chain of atoms joined by links of equal length. The links are assumed to be subject to random shocks, that force the atoms to move and the molecule to diffuse. The shock mechanism is different according to whether the atom occupies an odd or an even position on the chain. The originating stochastic model is a randomized random walk on the integers with an unusual exponential pattern for the inter-step time intervals. The authors analyze some features of this process and investigate also its queue counterpart, where the walk is confined to the non negative integers. Stimulated by the above researches, a birth and death process N(t) on the integers with a transition rate λ from even states and a possibly different rate μ from odd states has been studied in the first part of the thesis. A de- tailed description of the model is performed, and the Chapman-Kolmogorov equations are introduced. Then, the probability generating functions of even and odd states are then obtained. These allow to evaluate the transition probabilities of the process for arbitrary integer initial state. Certain sym- metry properties of the transition probabilities are also pinpointed. Then, the birth and death process obtained by superimposing a reecting bound- ary in the zero-state is analyzed. In particular, by making use of a Laplace transform approach, the probability of a transition from state 0 or state 1 to the zero-state is obtained. Formulas for mean and variance of both processes are finally provided. The second part of the thesis is devoted to the analysis of a generalized telegraph process with an underlying random walk. The classical telegraph process describes a random motion on the real line characterized by two _nite velocities with opposite directions, where the velocity changes are governed by a time-homogeneous Poisson process (see Orsingher [2]). The novelty in the proposed model consists in the use of new rules for velocity changes, which are now governed by a sequence of Bernoulli trials. This implies that the random times separating consecutive changes of direction of the mov- ing particle have a general distribution and form a non-regular alternating renewal process. Starting from the origin, the running particle performs an alternating motion with velocities c and -v (c; v > 0). The direction of the motion (forward and backward) is determined by the velocity sign. The particle changes the direction according to the outcome of a Bernoulli trial. Hence, this defines a (possibly asymmetric) random walk governing the choice of the velocity at any epoch. By adopting techniques based on renewal theory, the general form of probability law is determined as well as the mean of the process. Furthermore, two instances are investigated in detail, in which the random intertimes between consecutive velocity changes are exponentially distributed with (i) constant rates and with (ii) linearly increasing rates. In the first case, explicit expressions of the transition den- sity and of the conditional mean of the process are expressed as series of Gauss hypergeometric functions. The second case leads to a damped ran- dom motion, for which we obtain the transition density in closed form. It is interesting to note that the latter case yields a logistic stationary density. References [1] Conolly B.W. (1971) On randomized random walks. SIAM Review, 13, 81-99. [2] Orsingher, E. (1990) Probability law, flow functions, maximum distri- bution of wave-governed random motions and their connections with Kirchoff's laws. Stoch. Process. Appl., 34, 49-66. [3] Parthasarathy P.R. and Lenin R.B. (2004) Birth and death process (BDP) models with applications-queueing, communication systems, chemical models, biological models: the state-of the- art with a time- dependent perspective. American Series in Mathematical and Manage- ment Sciences, vol. 51, American Sciences Press, Columbus (2004) [4] Stockmayer W.H., Gobush W. and Norvich R. (1971) Local-jump mod- els for chain dynamics. Pure Appl. Chem., 26, 555-561. NOTE The thesis consists of four chapters: Chapter 1. Some definitions and properties of stochastic processes. Chapter 2. Analysis of birth-death processes on the set of integers, char- acterized by alternating rates. Chapter 3. Results on the standard telegraph process. Chapter 4. Study of the telegraph process with an underlying random walk governing the velocity changes. [edited by author]
X n.s.
Elstro, Stephanie Jo. "25 Random Things About Me." Miami University / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=miami1250637568.
Full textJones, Elinor Mair. "Large deviations of random walks and levy processes." Thesis, University of Manchester, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.491853.
Full textBooks on the topic "Processi random"
Mix, Dwight F. Random signal processing. London: Prentice-Hall International, 1995.
Find full textRandom signal processing. Englewood Cliffs, N.J: Prentice Hall, 1995.
Find full textO'Flynn, Michael. Probabilities, random variables, and random processes: Digital and analog. New York: Wiley, 1990.
Find full textSkorokhod, A. V. Random processes with independent increments. Dordrecht: Kluwer Academic Publishers, 1991.
Find full textRandom processes: Filtering, estimation, and detection. Hoboken, N.J: Wiley-Interscience, 2003.
Find full textDavid, Stirzaker, ed. Probability and random processes. Oxford [England]: Clarendon Press, 1992.
Find full textDavid, Stirzaker, ed. Probability and random processes. 3rd ed. Oxford: Oxford University Press, 2001.
Find full textDavid, Stirzaker, ed. Probability and random processes. 2nd ed. Oxford: Clarendon Press, 1992.
Find full textGrimmett, Geoffrey. Probability and random processes. 3rd ed. Oxford: Oxford University Press, 2004.
Find full textPicinbono, Bernard. Random signals and systems. Englewood Cliffs, NJ: Prentice-Hall, 1993.
Find full textBook chapters on the topic "Processi random"
Gopi, E. S. "Random Process." In Mathematical Summary for Digital Signal Processing Applications with Matlab, 123–52. Dordrecht: Springer Netherlands, 2009. http://dx.doi.org/10.1007/978-90-481-3747-3_3.
Full textLalanne, Christian. "Statistical Properties of a Random Process." In Random Vibration, 1–77. Chichester, UK: John Wiley & Sons, Ltd, 2014. http://dx.doi.org/10.1002/9781118931158.ch1.
Full textMauro, Raffaele. "Counting Process." In Traffic and Random Processes, 63–78. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-09324-6_5.
Full textPreumont, André. "Gaussian Process, Poisson Process." In Random Vibration and Spectral Analysis, 57–74. Dordrecht: Springer Netherlands, 1994. http://dx.doi.org/10.1007/978-94-017-2840-9_4.
Full textHarwit, Martin. "Random Processes." In Astrophysical Concepts, 104–58. New York, NY: Springer New York, 1988. http://dx.doi.org/10.1007/978-1-4757-2019-8_4.
Full textCarlton, Matthew A., and Jay L. Devore. "Random Processes." In Probability with Applications in Engineering, Science, and Technology, 489–562. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-52401-6_7.
Full textGebali, Fayez. "Random Processes." In Analysis of Computer and Communication Networks, 1–16. Boston, MA: Springer US, 2008. http://dx.doi.org/10.1007/978-0-387-74437-7_2.
Full textHarwit, Martin. "Random Processes." In Astrophysical Concepts, 97–148. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-2928-3_4.
Full textCarlton, Matthew A., and Jay L. Devore. "Random Processes." In Probability with Applications in Engineering, Science, and Technology, 597–682. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0395-5_7.
Full textChonavel, Thierry. "Random Processes." In Statistical Signal Processing, 9–21. London: Springer London, 2002. http://dx.doi.org/10.1007/978-1-4471-0139-0_2.
Full textConference papers on the topic "Processi random"
Wilkowski, D., R. Kaiser, G. Labeyrie, C. A. Müller, Ch Miniatura, T. Wellens, B. Grémaud, and D. Delande. "Light transport in cold atoms: dephasing processes." In Photonic Metamaterials: From Random to Periodic. Washington, D.C.: OSA, 2007. http://dx.doi.org/10.1364/meta.2007.thc4.
Full textHoenders, Bernhard J. "The (Quasi) Natural Mode Description of the Scattering Process by Dispersive Photonic Crystals." In Photonic Metamaterials: From Random to Periodic. Washington, D.C.: OSA, 2006. http://dx.doi.org/10.1364/meta.2006.thd20.
Full textKorneev, Andrey, Tamara Lavrukhina, Mikhail Pantyushin, and Tatiana Smetannikova. "Simulation of High-Tech Equipment Maintenance Process Using Random Processes." In 2022 4th International Conference on Control Systems, Mathematical Modeling, Automation and Energy Efficiency (SUMMA). IEEE, 2022. http://dx.doi.org/10.1109/summa57301.2022.9973906.
Full textVélez, 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.
Full textGurov, Igor, Mikhail Taratin, and Alexey Zakharov. "Analysis and optimization of the computational process of nonlinear discrete Kalman filtering." In Saratov Fall Meeting 2004: Coherent Optics of Ordered and Random Media V, edited by Dmitry A. Zimnyakov. SPIE, 2005. http://dx.doi.org/10.1117/12.636871.
Full textTreviño, 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.
Full textLupenko, Serhii, Iaroslav Lytvynenko, and Nataliia Stadnyk. "Method of Statistical Processing of Discrete Cycle Random Processes, by their Reduction to Isomorphic Periodic Random Sequences." In 2020 10th International Conference on Advanced Computer Information Technologies (ACIT). IEEE, 2020. http://dx.doi.org/10.1109/acit49673.2020.9209004.
Full textDrignei, Dorin, Igor Baseski, Zissimos P. Mourelatos, and Vijitashwa Pandey. "A Random Process Metamodel for Time-Dependent Reliability of Dynamic Systems." In ASME 2014 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2014. http://dx.doi.org/10.1115/detc2014-34313.
Full textJing Pan, Jiashen Qin, Lei Ning, Yanbin Zheng, and Qun Ding. "Random process representations of chaos." In 2013 International Conference on Sensor Network Security Technology and Privacy Communication System (SNS & PCS). IEEE, 2013. http://dx.doi.org/10.1109/sns-pcs.2013.6553851.
Full textReboul, S., and D. Brige. "Optimal segmentation by random process fusion." In Proceedings of the Third International Conference on Information Fusion. IEEE, 2000. http://dx.doi.org/10.1109/ific.2000.862651.
Full textReports on the topic "Processi random"
Mayster, Penka, and Assen Tchorbadjieff. Supercritical Markov Branching Process with Random Initial Condition. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, February 2019. http://dx.doi.org/10.7546/crabs.2019.01.03.
Full textFreidlin, Mark. PDE's, Random Processes and Fields: Asymptotic Problems. Fort Belvoir, VA: Defense Technical Information Center, November 1995. http://dx.doi.org/10.21236/ada304572.
Full textLeadbetter, M. R. On the Exeedance Random Measures for Stationary Processes. Fort Belvoir, VA: Defense Technical Information Center, November 1987. http://dx.doi.org/10.21236/ada192838.
Full textVoychishin, K. S., and Ya P. Dragan. Elimination Of Rhythm For Periodically Correlated Random Processes. Fort Belvoir, VA: Defense Technical Information Center, January 1993. http://dx.doi.org/10.21236/ada261061.
Full textSlone, Dale M. Efficient biased random bit generation for parallel processing. Office of Scientific and Technical Information (OSTI), September 1994. http://dx.doi.org/10.2172/105005.
Full textYoung, Richard M. Modeling Random Walk Processes In Human Concept Learning. Fort Belvoir, VA: Defense Technical Information Center, May 2006. http://dx.doi.org/10.21236/ada462700.
Full textMichels, James H. Synthesis of Multichannel Autoregressive Random Processes and Ergodicity Considerations. Fort Belvoir, VA: Defense Technical Information Center, July 1990. http://dx.doi.org/10.21236/ada226493.
Full textSlavtchova-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, May 2021. http://dx.doi.org/10.7546/crabs.2021.05.03.
Full textAlfano, R. R., F. Liu, Y. Guo, C. H. Liu, and J. Ying. Optical Amplification and Nonlinear Optical Processes in Random Scattering Media. Fort Belvoir, VA: Defense Technical Information Center, April 2000. http://dx.doi.org/10.21236/ada377025.
Full textGetoor, R. K., and Joseph Glover. Constructing Markov Processes with Random Times of Birth and Death,. Fort Belvoir, VA: Defense Technical Information Center, January 1986. http://dx.doi.org/10.21236/ada171856.
Full text