We consider analysis of complex stochastic models based upon partial information. MCMC and reversible jump MCMC are often the methods of choice for such problems, but in some situations they can be difficult to implement; and suffer from problems such as poor mixing, and the difficulty of diagnosing convergence. Here we review three alternatives to MCMC methods: importance sampling, the forward...

We propose a simple and novel framework for MCMC inference in continuoustime discrete-state systems with pure jump trajectories. We construct an exact MCMC sampler for such systems by alternately sampling a random discretization of time given a trajectory of the system, and then a new trajectory given the discretization. The first step can be performed efficiently using properties of the Poisso...

We consider the optimal stopping problem for g(Zn), where Zn, n = 1, 2, . . . , is a homogeneous Markov sequence. An algorithm, called forward improvement iteration, is presented by which an optimal stopping time can be computed. Using an iterative step, this algorithm computes a sequence B0 ⊇ B1 ⊇ B2 ⊇ · · · of subsets of the state space such that the first entrance time into the intersection ...

We propose a kinetic model of a fluid in which five macroscopic fields, the mass, energy, and three components of momentum, are conserved. The dynamics is constructed using the methods of statistical dynamics, and results in a discrete-time Markov chain for random fields on a lattice, followed by projection onto the information manifold. In the continuum limit we obtain a non-linear coupled par...

In this paper, we investigate the behavior of block errors which arise in data transmission on fading channels. Our approach takes into account the details of the specific coding/modulation scheme and tracks the fading process symbol by symbol. It is shown that a Markov approximation for the block error process (possibly degenerating into an identically distributed (i.i.d.) process for sufficie...

The knowledge of the state sequences that explain a given observed sequence for a known hidden Markovian model is the basis of various methods that may be divided into three categories: (i) enumeration of state sequences; (ii) summary of the possible state sequences in state profiles; (iii) computation of a global measure of the state sequence uncertainty. Concerning the first category, the gen...

Many applications in computer animation portray the motion of a human arm and torso. Often such applications can benefit from a combination of Inverse (IK) and Forward (FK) Kinematics controls to manipulate the arms of the model. The human arm is a kinematic chain with seven degrees of freedom. The previous analytic solution to this kinematic chain gives highly detailed IK controls, but problem...

In this paper two methods are presented. The first is a kinematic evaluation method for two different hexapod structures: standard Stewart platform manipulator with extensible struts and second structure with fixed strut lengths but sliding guideways on fixed platform. The second method addresses the forward kinematic problem where different mathematical representations are combined with variou...

We propose a novel way for ambient assisted living: a system that with motion detector to observe the daily activities of the elderly, build the daily activity model of the user. In case of unusual activities the system send alarm signal to caregiver. The problems with this approach to build such a model: firstly, the activities of the user are random and dynamic distributed, that means the rel...