AbstractA noncommutative analog of the concept of Markov time is formulated, in association with a canonical Wiener process (P, Q) [4]. For such a Markov time T, the quantities PT(t) = P(t + T) − P(T), QT(t) = Q(t + T) − Q(T) can be defined using spectral integrals with operator-valued integrands, and constitute a new canonical Wiener process (PT, QT), which is independent of the analog of the σ-field of events generated by the process up to the Markov time
Let $X(t, omega) = {x_t(omega): t geq 0} be a Markov process defined on a probability space $(Omega,...
This work links the conditional probability structure of Lancaster probabilities to a construction o...
The Wiener process is characterized by martingale and reverse martingale property of some linear and...
AbstractContinuing an earlier work [4], properties of canonical Wiener processes are investigated. A...
This thesis introduces a type of Markov property, called the 'set-Markov' property, that can be defi...
The purpose of this paper is to get a canonical representation of Gaussian processes which are equiv...
Na początku zostały omówione podstawowe definicje i twierdzenia dotyczące procesów stochastycznych. ...
The Wiener process is the classical example of a mathematical model for Brownian movement. Wiener vi...
We give two characterisations of the finite Markov property for Gaussian processes indexed by , base...
A definition of stochastic discrete-time scale invariance Markov(DT-SIM) process is proposed and its...
A recent theorem in [3] provided a link between a certain function of transition probabilities of a ...
Simultaneous changes of time scales of the components of a vector Markov process are defined and dev...
© Copyright 2001 IEEEIn this article we consider a dynamic M-ary detection problem when Markov chain...
AbstractBy a Wiener process we mean a countably additive random measure taking independent values on...
The book presents an in-depth study of arbitrary one-dimensional continuous strong Markov processes ...
Let $X(t, omega) = {x_t(omega): t geq 0} be a Markov process defined on a probability space $(Omega,...
This work links the conditional probability structure of Lancaster probabilities to a construction o...
The Wiener process is characterized by martingale and reverse martingale property of some linear and...
AbstractContinuing an earlier work [4], properties of canonical Wiener processes are investigated. A...
This thesis introduces a type of Markov property, called the 'set-Markov' property, that can be defi...
The purpose of this paper is to get a canonical representation of Gaussian processes which are equiv...
Na początku zostały omówione podstawowe definicje i twierdzenia dotyczące procesów stochastycznych. ...
The Wiener process is the classical example of a mathematical model for Brownian movement. Wiener vi...
We give two characterisations of the finite Markov property for Gaussian processes indexed by , base...
A definition of stochastic discrete-time scale invariance Markov(DT-SIM) process is proposed and its...
A recent theorem in [3] provided a link between a certain function of transition probabilities of a ...
Simultaneous changes of time scales of the components of a vector Markov process are defined and dev...
© Copyright 2001 IEEEIn this article we consider a dynamic M-ary detection problem when Markov chain...
AbstractBy a Wiener process we mean a countably additive random measure taking independent values on...
The book presents an in-depth study of arbitrary one-dimensional continuous strong Markov processes ...
Let $X(t, omega) = {x_t(omega): t geq 0} be a Markov process defined on a probability space $(Omega,...
This work links the conditional probability structure of Lancaster probabilities to a construction o...
The Wiener process is characterized by martingale and reverse martingale property of some linear and...