A discrete Markov process corresponds to the complex chemical reaction in the model i.e. the concentrations of the components are discrete quantities. The differences between the stochastic and deterministic models are discussed. . , .. . .
The relation between Markovianity and representability by means of first-order PDEs is investigated. We consider two versions of the Markovian property, weak and strong-Markovianity. The weak version has been introduced in (J.C. Willems, State and first-order representations, in: V.D. Blondel,...
Stabilization of Discontinuous Singular Systems with Markovian Switching and saturating inputs In this paper, the problem of stochastic stability and stochastic stabilization of Markov jumping singular systems with discontinuities and saturating inpu... J Raouf,EK Boukas - American Control Conference 被引量...
This results in a conditionally Markovian model of credit risk. We then combine our model of credit risk with a model of interest rate risk in order to derive an arbitrage鈥恌ree model of defaultable bonds. As expected, the market price processes of interest rate risk and credit risk provide...
the probability of the process never having crossed a given leveluis approximated as the probability that all members of the set of amplitude (or envelope) values at a discrete set of time values are belowu, along with the assumption that the set of amplitude values has Markovian conditioning....
17of searching for a hidden target by a single calcium ion. An analytical solution to this problem was found and then coupled with a Markovian jump process to model buffering and calcium influx18. Despite its advantages, this hybrid method does not account for thesensor’s binding and un...
Here, we introduce a theoretical framework that enables the non-perturbative determination of persistence exponents of Gaussian non-Markovian processes with non stationary dynamics relaxing to a steady state after an initial perturbation. Two situations are analyzed: either the system is subjected to a ...
LGM, last glacial maximum (∼ 0.02 MYA); MIS 4, marine oxygen isotope stage 4 (0.05–0.075 MYA); PG, penultimate glaciation (0.13–0.3 MYA); QM, Qingzang movement (1.7–3.6 MYA); PSMC, pairwise sequential markovian coalescent; MYA, million years ago. To examine the changes in ...
Jordan. Learning Without State-Estimation in Partially Observable Markovian Decision Processes. In Pro- ceedings of the 11th International Conference on Machine Learning, 1994. 19. Daniel Szer, Fran¸cois Charpillet, and Shlomo Zilberstein. MAA*: A heuristic search algorithm for solving ...
In this case, P(N/Ti) is a counting process for Markovian events where the average rate is 1/s in the decay time Ti of state i. The mean particle displace- ment (first moment) and spread (second moment) of the 1-D steady state parent profile have been deter- mined [Zoia, 2008]...