Lifted inference has been proposed for various probabilistic logical frameworks in order to compute the probability of queries in a time that depends on the size of the domains of the random variables rather than the number of instances. Even if various authors have underlined its importance for probabilistic logic programming (PLP), lifted inference has been applied up to now only to relationa...

This work presents a real-time active vision tracking system based on log-polar image motion estimation with 2D geometric deformation models. We present a very efficient parametric motion estimation method, where most computation can be done offline. We propose a redundant parameterization for the geometric deformations, which improve the convergence range of the algorithm. A foveated image rep...

In this article we discuss estimation of the common variance of several normal populations with tree order restricted means. We discuss the asymptotic properties of the maximum likelihood estimator of the variance as the number of populations tends to infinity. We consider several cases of various orders of the sample sizes and show that the maximum likelihood estimator of the variance may or m...

SNR (Signal to Noise Ratio) estimation is a very important parameter for channel estimation of the communication system. In this paper, some SNR estimation methods of digital modulation system are applied and improved in FM modulation system. Then we summarize several SNR estimation methods (EHM (Envelope High order Moment method), SE (Spectrum Estimation method), FD (Frequency Domain method), ...

This study demonstrated the equivalence between the Rasch testlet model and the three-level one-parameter testlet model and explored the Markov Chain Monte Carlo (MCMC) method for model parameter estimation in WINBUGS. The estimation accuracy from the MCMC method was compared with those from the marginalized maximum likelihood estimation (MMLE) with the expectation-maximization algorithm in Con...

This paper is concerned with the probability-constrained filtering problem for a class of time-varying nonlinear stochastic systems with estimation error variance constraint. The stochastic nonlinearity considered is quite general that is capable of describing several well-studied stochastic nonlinear systems. The second-order statistics of the noise sequence are unknown but belong to certain k...