29,384 research outputs found
Markov Constraints for Generating Lyrics with Style
No full textWe address the issue of generating texts in the style of an
existing author, that also satisfy structural constraints imposed by the
genre of the text. We focus on song lyrics, for which structural constraints
are well-defined: rhyme and meter. Although Markov processes
are known to be suitable for representing style, they are difficult
to control in order to satisfy non-local properties, such as structural
constraints, that require long distance modeling. We show that
the framework of Constrained Markov Processes allows us to precisely
generate texts that are consistent with a corpus, while being
controllable in terms of rhymes and meter, a result that no other technique,
to our knowledge, could achieve to date. Controlled Markov
processes consist in reformulating Markov processes in the context
of constraint satisfaction. We describe how to represent stylistic and
structural properties in terms of constraints in this framework and
we provide an evaluation of our method by comparing it to both pure
Markov and pure constraint-based approaches.We show how this approach
can be used for the semi-automatic generation of lyrics in the
style of a popular author that has the same structure as an existing
son
Asymptotic stability analysis of nonlinear stochastic semi-Markov jump systems
No full textIn this article, three different types of stochastic asymptotic stability for nonlinear stochastic semi-Markov jump systems (SSMJS) are investigated. Novel sufficient conditions for pth (p>0) \left(p>0\right) -moment asymptotic stability, almost sure asymptotic stability and stochastic asymptotic stability in the large are obtained. It is remarkable that the obtained results in the latter case cover the results in existing literature. Finally, two examples are presented to confirm the validity of the obtained theoretical results
Necessary and sufficient conditions for moment stability of positive Markov jump linear systems
No full textThis paper focuses on the problems of stability for positive Markov jump linear systems (PMJLSs) and its application to nonlinear Markov jump stochastic systems (MJSSs). First, we provide sufficient and necessary conditions for p -moment exponential stability of PMJLS. Then, based on the proposed results on p-moment exponential stability of PMJLS, we obtain explicit stability criteria for nonlinear MJSSs. Finally, two numerical examples are presented to confirm the validity of the obtained theoretical results.(c) 2022 Elsevier Ltd. All rights reserved
CLTs and asymptotic variance of time-sampled Markov chains
No full textFor a Markov transition kernel P and a probability distribution
μ on nonnegative integers, a time-sampled Markov chain evolves according
to the transition kernel Pμ = Σkμ(k)Pk. In this note we obtain CLT
conditions for time-sampled Markov chains and derive a spectral formula
for the asymptotic variance. Using these results we compare efficiency of
Barker's and Metropolis algorithms in terms of asymptotic variance
A statistical multiresolution approach for face recognition using structural hidden Markov models
No full textThis paper introduces a novel methodology that combines the multiresolution feature of the discrete wavelet transform (DWT) with the local interactions of the facial structures expressed through the structural hidden Markov model (SHMM). A range of wavelet filters such as Haar, biorthogonal 9/7, and Coiflet, as well as Gabor, have been implemented in order to search for the best performance. SHMMs perform a thorough probabilistic analysis of any sequential pattern by revealing both its inner and outer structures simultaneously. Unlike traditional HMMs, the SHMMs do not perform the state conditional independence of the visible observation sequence assumption. This is achieved via the concept of local structures introduced by the SHMMs. Therefore, the long-range dependency problem inherent to traditional HMMs has been drastically reduced. SHMMs have not previously been applied to the problem of face identification. The results reported in this application have shown that SHMM outperforms the traditional hidden Markov model with a 73% increase in accuracy
Nonlinearly Perturbed Birth-Death-Type Semi-Markov Processes
No full textIn Chapter 5, we present asymptotic expansions for stationary and conditional quasi-stationary distributions of nonlinearly perturbed birth-death-type semi-Markov processes, which play an important role in many applications. In this case, the corresponding expansions can be given in a more explicit form. © 2017, The Author(s).</p
Asymptotic Expansions for Moments of Hitting Times for Nonlinearly Perturbed Semi-Markov Processes
No full textIn Chapter 3, we introduce a model of perturbed semi-Markov processes, formulate basic perturbation conditions, describe a one-step time-space screening procedure of phase space reduction for perturbed semi-Markov processes, introduce hitting times, and prove an invariant property of them with respect to the procedure of phase space reduction. We, also, present algorithms for re-calculation of asymptotic expansions for transition characteristics of nonlinearly perturbed semi-Markov processes with reduced phase spaces and algorithms for sequential reduction of phase space for semi-Markov processes and construction of Laurent asymptotic expansions, without and with explicit upper bounds for remainders, for power moment of hitting times. © 2017, The Author(s).</p
Analysis of a two-stage queueing system with a Markov arrival and service processes in discrete time
No full textA two-stage queueing system with one server and
a buffer of finite capacity in each stage and with a discrete
Markov flow of customers is considered. If at the transition
moment of a customer to the second stage, the server and all
waiting places in the second stage are occupied, this customer
is lost. The algorithm to calculate the stationary state probabilities
of the number of customers in each stage at an arbitrary
discrete time moment is derived. Expressions for loss
probabilities are obtained
Markov switching MIDAS models
No full textRevised version of EUI ECO WP 2011/03.
Accepted author version posted online: 12 Sep 2012.
Published online: 28 Jan 2013.This article introduces a new regression model—Markov-switching mixed data sampling (MS-MIDAS)—that incorporates regime changes in the parameters of the mixed data sampling (MIDAS) models and allows for the use of mixed-frequency data in Markov-switching models. After a discussion of estimation and inference for MS-MIDAS and a small sample simulation-based evaluation, the MS-MIDAS model is applied to the prediction of the U.S. economic activity, in terms of both quantitative forecasts of the aggregate economic activity and the prediction of the business cycle regimes. Both simulation and empirical results indicate that MS-MIDAS is a very useful specification
Eaton's Markov chain, its conjugate partner and P-admissibility
No full textSuppose that X is a random variable with density f(xj`) and that ��(`jx) is a proper posterior corresponding to an improper prior (`). The prior is called P-admissible if the generalized Bayes estimator of every bounded function of ` is almost--admissible under squared error loss. Eaton (1992) showed that recurrence of the Markov chain with transition density R(jj`) = R ��(jjx)f(xj`)dx is a sufficient condition for P-admissibility of (`). We show that Eaton's Markov chain is recurrent if and only if its conjugate partner, with transition densit
- …
