Relationship Between Perturbation Realization Factors With Queueing Models and Markov Models

2006 ◽  
Vol 51 (10) ◽  
pp. 1699-1704 ◽  
Author(s):  
L. Xia ◽  
X.-R. Cao
Keyword(s):  
Markov Models ◽  
Queueing Models ◽  
Realization Factors ◽  
Perturbation Realization

scholarly journals Self-Similar Markovian Sources

2020 ◽  
Vol 10 (11) ◽  
pp. 3727 ◽  
Author(s):  
Adam Domański ◽  
Joanna Domańska ◽  
Katarzyna Filus ◽  
Jakub Szyguła ◽  
Tadeusz Czachórski
Keyword(s):  
Long Range ◽  
Computer Networks ◽  
Markov Models ◽  
Internet Traffic ◽  
Similar Process ◽  
Queueing Models ◽  
Network Structures ◽  
Self Similarity ◽  
Self Similar

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 comparable with those achieved using a well-known generator of self-similar traffic.

Transition (markov) models for the analysis of survival times in clinical research

1999 ◽  
Vol 28 (1) ◽  
pp. 165-176
Author(s):  
Sati Mazumdar ◽  
Kenneth Liu ◽  
Sang Ahnn ◽  
Patricia R. Houck ◽  
Charles F. Reynolds
Keyword(s):  
Clinical Research ◽  
Markov Models ◽  
Survival Times

Markov models—Markov chains

2019 ◽  
Vol 16 (8) ◽  
pp. 663-664 ◽  
Author(s):  
Jasleen K. Grewal ◽  
Martin Krzywinski ◽  
Naomi Altman
Keyword(s):  
Markov Chains ◽  
Markov Models

Estimating Personality Impression from Speech Record Using Hidden Markov Models

2015 ◽  
Vol 135 (12) ◽  
pp. 1517-1523 ◽  
Author(s):  
Yicheng Jin ◽  
Takuto Sakuma ◽  
Shohei Kato ◽  
Tsutomu Kunitachi
Keyword(s):  
Hidden Markov Models ◽  
Markov Models ◽  
Hidden Markov

Hidden Markov Processes

2014 ◽  
Author(s):  
M. Vidyasagar
Keyword(s):  
Hidden Markov Models ◽  
Markov Processes ◽  
Viterbi Algorithm ◽  
Markov Models ◽  
Hidden Markov ◽  
Local Alignment ◽  
Biological Applications ◽  
Standard Material ◽  
Hidden Markov Processes ◽  
Genomics And Proteomics

This book explores important aspects of Markov and hidden Markov processes and the applications of these ideas to various problems in computational biology. It starts from first principles, so that no previous knowledge of probability is necessary. However, the work is rigorous and mathematical, making it useful to engineers and mathematicians, even those not interested in biological applications. A range of exercises is provided, including drills to familiarize the reader with concepts and more advanced problems that require deep thinking about the theory. Biological applications are taken from post-genomic biology, especially genomics and proteomics. The topics examined include standard material such as the Perron–Frobenius theorem, transient and recurrent states, hitting probabilities and hitting times, maximum likelihood estimation, the Viterbi algorithm, and the Baum–Welch algorithm. The book contains discussions of extremely useful topics not usually seen at the basic level, such as ergodicity of Markov processes, Markov Chain Monte Carlo (MCMC), information theory, and large deviation theory for both i.i.d and Markov processes. It also presents state-of-the-art realization theory for hidden Markov models. Among biological applications, it offers an in-depth look at the BLAST (Basic Local Alignment Search Technique) algorithm, including a comprehensive explanation of the underlying theory. Other applications such as profile hidden Markov models are also explored.

APPLICATION OF MULTI-STATE SEMI-MARKOV MODELS ON HIV/AIDS DISEASE PROGRESSION

2018 ◽  
Vol 7 (3) ◽  
pp. 30
Author(s):  
KALAYU MENGESHA SOLOMON ◽  
ALEMU GEBREMEDHN GEBREGEWERGIS ◽  
FEREDE TILAHUN ◽  
ATSMEGIORGIS CHERU ◽  
◽  
...  
Keyword(s):  
Disease Progression ◽  
Markov Models ◽  
Hiv Aids
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