Gotowe bibliografie tematyczne / Modelling, Markov chain

Spis treści

  1. Artykuły w czasopismach
  2. Rozprawy doktorskie
  3. Książki
  4. Części książek
  5. Streszczenia konferencji

Gotowa bibliografia na temat „Modelling, Markov chain”

Autor: Grafiati
Data publikacji: 4 czerwca 2021
Data aktualizacji: 1 lutego 2022

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Artykuły w czasopismach na temat "Modelling, Markov chain"

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BOUCHER, THOMAS R., and DAREN B. H. CLINE. "PIGGYBACKING THRESHOLD PROCESSES WITH A FINITE STATE MARKOV CHAIN." Stochastics and Dynamics 09, no. 02 (June 2009): 187–204. http://dx.doi.org/10.1142/s0219493709002622.

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The state-space representations of certain nonlinear autoregressive time series are general state Markov chains. The transitions of a general state Markov chain among regions in its state-space can be modeled with the transitions among states of a finite state Markov chain. Stability of the time series is then informed by the stationary distributions of the finite state Markov chain. This approach generalizes some previous results.
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Gerontidis, Ioannis I. "Semi-Markov Replacement Chains." Advances in Applied Probability 26, no. 03 (September 1994): 728–55. http://dx.doi.org/10.1017/s0001867800026525.

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We consider an absorbing semi-Markov chain for which each time absorption occurs there is a resetting of the chain according to some initial (replacement) distribution. The new process is a semi-Markov replacement chain and we study its properties in terms of those of the imbedded Markov replacement chain. A time-dependent version of the model is also defined and analysed asymptotically for two types of environmental behaviour, i.e. either convergent or cyclic. The results contribute to the control theory of semi-Markov chains and extend in a natural manner a wide variety of applied probabilit
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Gerontidis, Ioannis I. "Semi-Markov Replacement Chains." Advances in Applied Probability 26, no. 3 (September 1994): 728–55. http://dx.doi.org/10.2307/1427818.

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We consider an absorbing semi-Markov chain for which each time absorption occurs there is a resetting of the chain according to some initial (replacement) distribution. The new process is a semi-Markov replacement chain and we study its properties in terms of those of the imbedded Markov replacement chain. A time-dependent version of the model is also defined and analysed asymptotically for two types of environmental behaviour, i.e. either convergent or cyclic. The results contribute to the control theory of semi-Markov chains and extend in a natural manner a wide variety of applied probabilit
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Faddy, M. J., and S. I. McClean. "Markov Chain Modelling for Geriatric Patient Care." Methods of Information in Medicine 44, no. 03 (2005): 369–73. http://dx.doi.org/10.1055/s-0038-1633979.

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Summary Objectives: To show that Markov chain modelling can be applied to data on geriatric patients and use these models to assess the effects of covariates. Methods: Phase-type distributions were fitted by maximum likelihood to data on times spent by the patients in hospital and in community-based care. Data on the different events that ended the patients’ periods of care were used to estimate the dependence of the probabilities of these events on the phase from which the time in care ended. The age of the patients at admission to care and the year of admission were also included as covariat
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SINGHAL, EKTA, and Kunal Mehta. "Marketing Channel Attribution Modelling: Markov Chain Analysis." International Journal of Indian Culture and Business Management 1, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijicbm.2020.10027991.

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Mehta, Kunal, and Ekta Singhal. "Marketing channel attribution modelling: Markov chain analysis." International Journal of Indian Culture and Business Management 21, no. 1 (2020): 63. http://dx.doi.org/10.1504/ijicbm.2020.109344.

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Hadjinicola, George, and Larry Goldstein. "Markov chain modelling of bioassay toxicity procedures." Statistics in Medicine 12, no. 7 (April 15, 1993): 661–74. http://dx.doi.org/10.1002/sim.4780120705.

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Catak, Muammer, Nurşin Baş, Kevin Cronin, Dario Tellez-Medina, Edmond P. Byrne, and John J. Fitzpatrick. "Markov chain modelling of fluidised bed granulation." Chemical Engineering Journal 164, no. 2-3 (November 1, 2010): 403–9. http://dx.doi.org/10.1016/j.cej.2010.02.022.

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Huang, Vincent, and James Unwin. "Markov chain models of refugee migration data." IMA Journal of Applied Mathematics 85, no. 6 (September 29, 2020): 892–912. http://dx.doi.org/10.1093/imamat/hxaa032.

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Abstract The application of Markov chains to modelling refugee crises is explored, focusing on local migration of individuals at the level of cities and days. As an explicit example, we apply the Markov chains migration model developed here to United Nations High Commissioner for Refugees data on the Burundi refugee crisis. We compare our method to a state-of-the-art ‘agent-based’ model of Burundi refugee movements, and highlight that Markov chain approaches presented here can improve the match to data while simultaneously being more algorithmically efficient.
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Balzter, Heiko. "Markov chain models for vegetation dynamics." Ecological Modelling 126, no. 2-3 (February 2000): 139–54. http://dx.doi.org/10.1016/s0304-3800(00)00262-3.

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Rozprawy doktorskie na temat "Modelling, Markov chain"

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Samci, Karadeniz Rukiye. "Modelling share prices as a random walk on a Markov chain." Thesis, University of Leicester, 2017. http://hdl.handle.net/2381/40129.

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In the financial area, a simple but also realistic means of modelling real data is very important. Several approaches are considered to model and analyse the data presented herein. We start by considering a random walk on an additive functional of a discrete time Markov chain perturbed by Gaussian noise as a model for the data as working with a continuous time model is more convenient for option prices. Therefore, we consider the renowned (and open) embedding problem for Markov chains: not every discrete time Markov chain has an underlying continuous time Markov chain. One of the main goals of
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Gallagher, Raymond. "Uncertainty modelling in quantitative risk analysis." Thesis, University of Liverpool, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.367676.

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Pang, Wan-Kai. "Modelling ordinal categorical data : a Gibbs sampler approach." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.323876.

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Kawale, Sujay J. "Implication of Terrain Topology Modelling on Ground Vehicle Reliability." Thesis, Virginia Tech, 2010. http://hdl.handle.net/10919/31241.

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The accuracy of computer-based ground vehicle durability and ride quality simulations depends on accurate representation of road surface topology as an excitation to vehicle dynamics simulation software, since most of the excitation input to a vehicle as it traverses terrain is provided by the surface topology. It is not computationally efficient to utilise physically measured terrain topology for these simulations since extremely large data sets would be required to represent terrain of all desired types. Moreover, performing repeated simulations on the same set of measured data would not p
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Bray, Isabelle Cella. "Modelling the prevalence of Down syndrome with applications of Markov chain Monte Carlo methods." Thesis, University of Plymouth, 1998. http://hdl.handle.net/10026.1/2408.

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This thesis was motivated by applications in the epidemiology of Down syndrome and prenatal screening for Down syndrome. Methodological problems arising in these applications include under-ascertainment of cases in livebirth studies, double-sampled data with missing observations and coarsening of data. These issues are considered from a classical perspective using maximum likelihood and from a Bayesian viewpoint employing Markov chain Monte Carlo (MCMC) techniques. Livebirth prevalence studies published in the literature used a variety of data collection methods and many are of uncertain compl
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Loza, Reyes Elisa. "Classification of phylogenetic data via Bayesian mixture modelling." Thesis, University of Bath, 2010. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.519916.

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Conventional probabilistic models for phylogenetic inference assume that an evolutionary tree,andasinglesetofbranchlengthsandstochasticprocessofDNA evolutionare sufficient to characterise the generating process across an entire DNA alignment. Unfortunately such a simplistic, homogeneous formulation may be a poor description of reality when the data arise from heterogeneous processes. A well-known example is when sites evolve at heterogeneous rates. This thesis is a contribution to the modelling and understanding of heterogeneityin phylogenetic data. Weproposea methodfor the classificationof DN
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Garzon, Rozo Betty Johanna. "Modelling operational risk using skew t-copulas and Bayesian inference." Thesis, University of Edinburgh, 2016. http://hdl.handle.net/1842/25751.

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Operational risk losses are heavy tailed and are likely to be asymmetric and extremely dependent among business lines/event types. The analysis of dependence via copula models has been focussed on the bivariate case mainly. In the vast majority of instances symmetric elliptical copulas are employed to model dependence for severities. This thesis proposes a new methodology to assess, in a multivariate way, the asymmetry and extreme dependence between severities, and to calculate the capital for operational risk. This methodology simultaneously uses (i) several parametric distributions and an al
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Bleki, Zolisa. "Efficient Bayesian analysis of spatial occupancy models." Master's thesis, University of Cape Town, 2020. http://hdl.handle.net/11427/32469.

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Species conservation initiatives play an important role in ecological studies. Occupancy models have been a useful tool for ecologists to make inference about species distribution and occurrence. Bayesian methodology is a popular framework used to model the relationship between species and environmental variables. In this dissertation we develop a Gibbs sampling method using a logit link function in order to model posterior parameters of the single-season spatial occupancy model. We incorporate the widely used Intrinsic Conditional Autoregressive (ICAR) prior model to specify the spatial rando
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Henriques, Bruno M. "Hybrid galaxy evolution modelling : Monte Carlo Markov Chain parameter estimation in semi-analytic models of galaxy formation." Thesis, University of Sussex, 2010. http://sro.sussex.ac.uk/id/eprint/2334/.

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We introduce a statistical exploration of the parameter space of the Munich semi-analytic model built upon the Millennium dark matter simulation. This is achieved by applying a Monte Carlo Markov Chain (MCMC) method to constrain the 6 free parameters that define the stellar mass function at redshift zero. The model is tested against three different observational data sets, including the galaxy K-band luminosity function, B −V colours, and the black hole-bulge mass relation, to obtain mean values, confidence limits and likelihood contours for the best fit model. We discuss how the model paramet
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Dao, Trong Nghia Electrical Engineering &amp Telecommunications Faculty of Engineering UNSW. "Modelling 802.11 networks for multimedia applications." Publisher:University of New South Wales. Electrical Engineering & Telecommunications, 2008. http://handle.unsw.edu.au/1959.4/41222.

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This thesis is concerned with the development of new mathematical models for the IEEE 802.11??s access mechanisms, with a particular focus on DCF and EDCA. Accurate mathematical models for the DCF and EDCA access mechanisms provide many benefits, such as improved performance analysis, easier network capacity planning, and robust network design. A feature that permeates the work presented in this thesis is the application of our new models to network environments where both saturated and non-saturated traffic sources are present. The scenario in which multiple traffic sources are present is mor
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Książki na temat "Modelling, Markov chain"

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Groen, Maria Margaretha de. Modelling interception and transpiration at monthly time steps: Introducing daily variability through Markov chains. Lisse: Swets & Zeitlinger, 2002.

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Winkler, Gerhard. Image Analysis, Random Fields and Markov Chain Monte Carlo Methods: A Mathematical Introduction (Stochastic Modelling and Applied Probability). 2nd ed. Springer, 2006.

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Quintana, José Mario, Carlos Carvalho, James Scott, and Thomas Costigliola. Extracting S&P500 and NASDAQ Volatility: The Credit Crisis of 2007–2008. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.13.

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This article demonstrates the utility of Bayesian modelling and inference in financial market volatility analysis, using the 2007-2008 credit crisis as a case study. It first describes the applied problem and goal of the Bayesian analysis before introducing the sequential estimation models. It then discusses the simulation-based methodology for inference, including Markov chain Monte Carlo (MCMC) and particle filtering methods for filtering and parameter learning. In the study, Bayesian sequential model choice techniques are used to estimate volatility and volatility dynamics for daily data fo
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Lopes, Hedibert, and Nicholas Polson. Analysis of economic data with multiscale spatio-temporal models. Edited by Anthony O'Hagan and Mike West. Oxford University Press, 2018. http://dx.doi.org/10.1093/oxfordhb/9780198703174.013.12.

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This article discusses the use of Bayesian multiscale spatio-temporal models for the analysis of economic data. It demonstrates the utility of a general modelling approach for multiscale analysis of spatio-temporal processes with areal data observations in an economic study of agricultural production in the Brazilian state of Espìrito Santo during the period 1990–2005. The article first describes multiscale factorizations for spatial processes before presenting an exploratory multiscale data analysis and explaining the motivation for multiscale spatio-temporal models. It then examines the temp
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Discrete-Time Markov Chains: Two-Time-Scale Methods and Applications (Stochastic Modelling and Applied Probability). Springer, 2004.

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Zhang, Qing, and George G. Yin. Continuous-Time Markov Chains and Applications: A Singular Perturbation Approach (Stochastic Modelling and Applied Probability). Springer, 1997.

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Zhang, Qing, and G. George Yin. Discrete-Time Markov Chains: Two-Time-Scale Methods and Applications (Stochastic Modelling and Applied Probability Book 55). Springer New York, 2006.

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Części książek na temat "Modelling, Markov chain"

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Asmussen, Søren, and Peter W. Glynn. "Markov Chain Monte Carlo Methods." In Stochastic Modelling and Applied Probability, 350–80. New York, NY: Springer New York, 2007. http://dx.doi.org/10.1007/978-0-387-69033-9_13.

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Suman, S. K., and S. Sinha. "Pavement Performance Modelling Using Markov Chain." In Proceedings of the International Symposium on Engineering under Uncertainty: Safety Assessment and Management (ISEUSAM - 2012), 619–27. India: Springer India, 2012. http://dx.doi.org/10.1007/978-81-322-0757-3_39.

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Maione, B., M. P. Fanti, and B. Turchiano. "Large Scale Markov Chain Modelling of Transfer Lines." In Operations Research Models in Flexible Manufacturing Systems, 193–211. Vienna: Springer Vienna, 1989. http://dx.doi.org/10.1007/978-3-7091-2654-7_9.

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Derouault, Anne-Marie, and Bernard Merialdo. "Language modelling using a hidden Markov chain with application to automatic transcription of French stenotypy." In Semi-Markov Models, 475–85. Boston, MA: Springer US, 1986. http://dx.doi.org/10.1007/978-1-4899-0574-1_29.

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Petrov, Tatjana. "Markov Chain Aggregation and Its Application to Rule-Based Modelling." In Modeling Biomolecular Site Dynamics, 297–313. New York, NY: Springer New York, 2019. http://dx.doi.org/10.1007/978-1-4939-9102-0_14.

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Strickland, Christopher M., Robert J. Denham, Clair L. Alston, and Kerrie L. Mengersen. "A Python Package for Bayesian Estimation Using Markov Chain Monte Carlo." In Case Studies in Bayesian Statistical Modelling and Analysis, 421–60. Chichester, UK: John Wiley & Sons, Ltd, 2012. http://dx.doi.org/10.1002/9781118394472.ch25.

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Conejo, S., A. Morata, and F. Valero. "First Order Markov Chain Model and Rainfall Sequences in several Stations of Spain." In Detecting and Modelling Regional Climate Change, 417–28. Berlin, Heidelberg: Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04313-4_36.

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Balaji Rao, K. "Markov Chain Modelling of Evolution of Deflection in Ferrocement Flexural Members." In Emerging Trends of Advanced Composite Materials in Structural Applications, 67–96. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-16-1688-4_3.

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Chotard, Alexandre, and Martin Holeňa. "A Generalized Markov-Chain Modelling Approach to (1,λ)-ES Linear Optimization." In Parallel Problem Solving from Nature – PPSN XIII, 902–11. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10762-2_89.

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Han, Zhonghua, Yuehan Liu, Haibo Shi, and Xutian Tian. "A Dynamic Buffer Reservation Method Based on Markov Chain to Solve Deadlock Problem in Scheduling." In Proceedings of the 11th International Conference on Modelling, Identification and Control (ICMIC2019), 1205–13. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0474-7_113.

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Streszczenia konferencji na temat "Modelling, Markov chain"

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Waller, Ephraim Nii Kpakpo, Pamela Delali Adablah, and Quist-Aphetsi Kester. "Markov Chain: Forecasting Economic Variables." In 2019 International Conference on Computing, Computational Modelling and Applications (ICCMA). IEEE, 2019. http://dx.doi.org/10.1109/iccma.2019.00026.

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Perera, Supun, Michael G. H. Bell, Fumitaka Kurauchi, and Dharshana Kasthurirathna. "Absorbing Markov Chain Approach to Modelling Disruptions in Supply Chain Networks." In 2019 Moratuwa Engineering Research Conference (MERCon). IEEE, 2019. http://dx.doi.org/10.1109/mercon.2019.8818809.

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Raj, Akash, and SMAK Azad. "Markov Chain Modelling of Standby Redundant Networked Control System." In 2019 Fifth International Conference on Electrical Energy Systems (ICEES). IEEE, 2019. http://dx.doi.org/10.1109/icees.2019.8719303.

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Winkovich, T., and D. Eckardt. "Reliability analysis of safety systems using Markov-chain modelling." In 2005 IEEE 11th European Conference on Power Electronics and Applications. IEEE, 2005. http://dx.doi.org/10.1109/epe.2005.219620.

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Mapp, Glenford, Dhawal Thakker, and Orhan Gemikonakli. "Exploring a New Markov Chain Model for Multiqueue Systems." In 2010 12th International Conference on Computer Modelling and Simulation. IEEE, 2010. http://dx.doi.org/10.1109/uksim.2010.113.

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Popa, D., and J. Tomasik. "On Markov Chain Modelling of Asynchronous Optical CSMA/CA Protocol." In 2007 15th International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems (MASCOTS). IEEE, 2007. http://dx.doi.org/10.1109/mascots.2007.44.

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Arkov, V. Yu, G. G. Kulikov, and T. V. Breikin. "Application of Markov Chains to Identification of Turbine Engine Dynamic Models." In ASME Turbo Expo 2002: Power for Land, Sea, and Air. ASMEDC, 2002. http://dx.doi.org/10.1115/gt2002-30038.

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The paper addresses the problem of dynamic modelling of gas turbines for condition monitoring purposes. Identification of dynamic models is performed using a novel Markov chain technique. This includes identifiability analysis and model estimation. When identifying the model, experimental data should be sufficiently informative for identification. So far, identifiability analysis is weak formed and workable solutions are still to be developed. A possible technique is proposed based on non-parametric models in the form of controllable Markov chains. The second step in systems identification is
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"Inverse of magnetic dipole field using a reversible jump Markov chain Monte Carlo." In 20th International Congress on Modelling and Simulation (MODSIM2013). Modelling and Simulation Society of Australia and New Zealand, 2013. http://dx.doi.org/10.36334/modsim.2013.a2.luo.

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Chan, Ronald, Pengfei Zhang, Wenyu Zhang, Ido Nevat, Alvin Valera, Hwee-Xian Tan, and Natarajan Gautam. "Adaptive duty cycling in sensor networks via Continuous Time Markov Chain modelling." In 2015 IEEE International Conference on Signal Processing for Communications (ICC). IEEE, 2015. http://dx.doi.org/10.1109/icc.2015.7249388.

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Datta, Soumendra Nath, Sowjanya Vankayalapati, Atanu Guchhait, Shekar Nethi, Sushanth Gajanan, Yongseok Park, Daekyu Choi, and Sang-Jun Moon. "Finite State Markov Chain modelling of IEEE TGn channels for packet level simulators." In 2014 International Conference on Signal Processing and Communications (SPCOM). IEEE, 2014. http://dx.doi.org/10.1109/spcom.2014.6983980.

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