Markov Chain
Cryptanalysis of a Markov Chain Based User Authentication Scheme
... In this paper, we have analyzed security pitfalls such as off-line password guessing attack, insider attack, insecurity on secret key and inefficient password change phase etc. of the recently pub- lished Djellali et ...
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Markov Chain Truncation for Doubly-Intractable Inference
... Markov Chain Monte Carlo (MCMC) algorithms can asymptotically draw samples from distributions with intractable normalizing constants. However, sampling from “doubly-intractable” distributions (Murray et ...
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The Superposition of Markov Chain and the Prediction of Consumer Price Index
... HEORY Markov chain model was first posed by Andre Markoff ...years, Markov chain model was applied to different fields ,such as economic, education, physics, genetics, computer and so ...
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COMPLEXITY OF EMBEDDED CHAIN ALGORITHM FOR COMPUTING STEADY STATE PROBABILITIES OF MARKOV CHAIN
... Markov chain. In the following analysis we assume, that underlying Markov chain has two states, which we denote as slow S, and fast ...underlying Markov chain is in state S, ...
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Scheduling Tasks with Markov-Chain Based Constraints
... To better understand the implications of MC constraints, we reproduce a figure from [15] in Figure 2(bottom). This figure depicts three curves corresponding to the system out- put signal power when the system dropout ...
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On Markov chain Monte Carlo methods for tall data
... Markov chain Monte Carlo methods are often deemed too computationally intensive to be of any practical use for big data applications, and in particular for inference on datasets containing a large number n ...
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1. Authorship attribution using markov chain
... Abstract- There are many important fields where authorship attribution is needed. It is the way of determining writer of a text when it is unclear. It is useful when two or more people claim to have written something or ...
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The flip Markov chain for connected regular graphs
... switch chain is a very natural Markov chain for sampling random regular ...switch chain is called a switch, in which two edges are deleted and replaced with two other edges, without changing ...
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Markov Chains. Chapter Introduction. Specifying a Markov Chain
... 30 (Coffman, Kaduta, and Shepp 16 ) A computing center keeps information on a tape in positions of unit length. During each time unit there is one request to occupy a unit of tape. When this arrives the first free unit ...
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A Markov Chain Approach to Study Replacement Model
... The Markov chain approach is applied to find the range for the number of defectives, beyond which, the manufacturing machine has to be replaced. Here the threshold values are found, where the upper ...
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Stochastic gradient Markov chain Monte Carlo
... Markov chain Monte Carlo (MCMC) algorithms are generally regarded as the gold standard technique for Bayesian ...gradient Markov chain Monte Carlo (SGMCMC) which utilises data subsampling ...
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Stability of sequential Markov Chain Monte Carlo methods
... Abstract. Sequential Monte Carlo Samplers are a class of stochastic algorithms for Monte Carlo integral estimation w.r.t. probability distributions, which combine elements of Markov chain Monte Carlo ...
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Non-linear Markov Chain Monte Carlo
... non-linear Markov Chain Monte Carlo (MCMC) methods for simulating from a probability measure ...Non-linear Markov kernels ...Self-Interacting Markov Chains (Del Moral & Miclo 2004) ...
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Relevant States and Memory in Markov Chain Bootstrapping and Simulation
... of Markov chain bootstrapping and ...In Markov chain bootstrapping the probability to re-generate large portions of the original series is a serious drawback, especially when the number of ...
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Derivatives pricing in a Markov chain jump diffusion setting
... In our MCJD model we consider a market in which there are several states of the market. Asset prices in the market follow a generalised geometric Brownian motion, with drift and volatility depending on the state of the ...
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Application of Weighted Markov Chain in Precipitation Forecast in Beijing
... Weighted Markov AR-GARCH-GED Model in the Prediction of ...fuzzy Markov chain model with weights and its application in predicting the precipitation ...
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Some limit properties for a hidden inhomogeneous Markov chain
... Hidden Markov chain is an important branch of Markov chain ...hidden Markov model was first introduced by Baum and Petrie ...geneous Markov chain (HTIMC) ...
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Uncovering mental representations with Markov chain Monte Carlo
... Markov chain Monte Carlo is one of the basic tools in modern statistical computing, providing the basis for numerical simulations conducted in a wide range of ...
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Markov chain approximations for transition densities of Lévy processes
... approximating Markov chain to the transition density of the Lévy process for the two proposed dis- cretisation schemes, one in the case where X has a non-trivial diffusion component and one when it does ...
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Markov chain approximations to scale functions of Lévy processes
... and [5, Chapter VII], while an excellent account of available numerical methods for computing them can be found in [21, Chapter 5]. Examples, few, but important, of processes when the scale functions can be given ...
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