Search results for "Markov"
showing 10 items of 628 documents
A mutual GrabCut method to solve co-segmentation
2013
Publised version of an article from the journal:Eurasip Journal on Image and Video Processing. Also available on SpringerLink:http://dx.doi.org/10.1186/1687-5281-2013-20. Open Access Co-segmentation aims at segmenting common objects from a group of images. Markov random field (MRF) has been widely used to solve co-segmentation, which introduces a global constraint to make the foreground similar to each other. However, it is difficult to minimize the new model. In this paper, we propose a new Markov random field-based co-segmentation model to solve co-segmentation problem without minimization problem. In our model, foreground similarity constraint is added into the unary term of MRF model ra…
Una metodologia per la suddivisione di un'area geografica regionale in Sistemi Turistici Locali.
2005
In questo lavoro si propone un metodo per a®rontare e risolvere il problema del dimensionamento e della localizzazione ottimali dei Sistemi Turistici Locali. A tal ¯ne, l'applicazione del modello proposto sull'area territoriale in esame viene iservata ad una fase in cui sono stati giµa presi in considerazione opzioni e vincoli trategici; viene presentato, invero, un criterio per la de¯nizione della gerarchia delle unitµa territoriali, che consente, d'altra parte, una sensibile riduzione delle alterna- ive ammissibili nella de¯nizione dei sistemi turistici, che avviene proponendo uno peci¯co algoritmo. l problema di ottimizzazione µe risolto successivamente mediante un procedimento di ricerc…
Markov Model for Tweets Geographic Distribution Characterization
2015
Abstract In this paper we will continue our researches regarding e-Business and e-Government modeling on Social Media presented in (Stoica, Pitic, & Mihaescu, 2013). Among message and user parameters we add a new parameter used to describe the geographical dispersion of Twitter messages. This new parameter will characterize the way one set of messages will spread in Social Graph from the physical word point of view. The first model, presented as “A Novel Model for E-Business and E-Government Processes on Social”, will be extended with the geographical parameter PG. We will define and we will describe the Markov Model used to organize the messages gathered from social media. The main idea of…
Towards a fuzzy-linguistic based social network sentiment-expression system
2015
Liking allows users of Social Networks, blogs and online magazines to express their support of posts and artifacts by a simple click. Such function is very popular but lacks semantic power, and some platforms have augmented it by allowing to choose a pictographic depiction corresponding to a feeling. What is gained in depth is lost in simplicity, and the wide acceptance liking has enjoyed did not carried to the sentiment version. We outline a sentiment-expression hybrid system based on textual analysis and linguistic fuzzy Markov chains overcoming the intrinsic limitations of liking without burdening the user with complex choices.
Usage of HMM-Based Speech Recognition Methods for Automated Determination of a Similarity Level Between Languages
2019
The problem of automated determination of language similarity (or even defining of a distance on the space of languages) could be solved in different ways – working with phonetic transcriptions, with speech recordings or both of them. For the recordings, we propose and test a HMM-based one: in the first part of our article we successfully try language detection, afterwards we are trying to calculate distances between HMM-based models, using different metrics and divergences. The Kullback-Leibler divergence is the only one we got good results with – it means that the calculated distances between languages correspond to analytical understanding of similarity between them. Even if it does not …
Non-Equilibrium Markov State Modeling of the Globule-Stretch Transition
2016
We describe a systematic approach to construct coarse-grained Markov state models from molecular dynamics data of systems driven into a nonequilibrium steady state. We apply this method to study the globule-stretch transition of a single tethered model polymer in shear flow. The folding and unfolding rates of the coarse-grained model agree with the original detailed model. We demonstrate that the folding and unfolding proceeds through the same narrow region of configuration space but along different cycles.
Unfolding dynamics of small peptides biased by constant mechanical forces
2018
We show how multi-ensemble Markov state models can be combined with constant-force equilibrium simulations. Besides obtaining the unfolding/folding rates, Markov state models allow gaining detailed insights into the folding dynamics and pathways through identifying folding intermediates and misfolded structures. For two specific peptides, we demonstrate that the end-to-end distance is an insufficient reaction coordinate. This problem is alleviated through constructing models with multiple collective variables, for which we employ the time-lagged independent component analysis requiring only minimal prior knowledge. Our results show that combining Markov state models with constant-force simu…
H<inf>&#x221E;</inf> filter design for time-delay Markovian jump systems
2013
This paper investigates the H ∞ filtering problem for discrete time-delay Markovian jump systems with application to networked control systems. To design a full-order filter which ensures the stochastic stability and a prescribed H ∞ performance level for the filtering error system, the Scaled Small Gain (SSG) Theorem is developed for stochastic systems. By employing a two-term approximation to delayed state variables, the original system is transformed into an input-output form consisting of two subsystems. Based on the developed SSG Theorem and the proposed Lyapunov-Krasovskii Functional (LKF), the scaled small gains of the subsystems are analyzed to establish a new condition for the exis…
Unary Probabilistic and Quantum Automata on Promise Problems
2015
We continue the systematic investigation of probabilistic and quantum finite automata (PFAs and QFAs) on promise problems by focusing on unary languages. We show that bounded-error QFAs are more powerful than PFAs. But, in contrary to the binary problems, the computational powers of Las-Vegas QFAs and bounded-error PFAs are equivalent to deterministic finite automata (DFAs). Lastly, we present a new family of unary promise problems with two parameters such that when fixing one parameter QFAs can be exponentially more succinct than PFAs and when fixing the other parameter PFAs can be exponentially more succinct than DFAs.
On Hagelbarger’s and Shannon’s matching pennies playing machines
2020
Abstract In the 1950s, Hagelbarger’s Sequence Extrapolating Robot (SEER) and Shannon’s Mind-Reading Machine (MRM) were the state-of-the-art research results in playing the well-known “matching pennies” game. In our research we perform a software implementation for both machines in order to test the common statement that MRM, even simpler, beats SEER. Also, we propose a simple contextual predictor (SCP) and use it to compete with SEER and MRM. As expected, experimental results proves the claimed MRM superiority over SEER and even the SCP’s superiority over both SEER and MRM. At the end, we draw some conclusions and propose further research ideas, like the use of mixing models methods and the…