The problem of estimating the number of states of a finite-alphabet, finite-state source is investigated. An estimator is developed that asymptotically attains the minimum probability of underestimating the number of states, among all estimators with a prescribed exponential decay rate of overestimation probability. The proposed estimator relies on the Lempel-Ziv data compression algorithm in a...

In the last few years, so called finite.state morphology, in general, and two-level morphology in particular, have become widely accepted as paradigms for the computational t reatment of morphology. Finite-state morphology appeals to the notion of a finite-state transducer, which is simply a classical finite-state automaton whose transitions are labeled with pairs, rather than with single symbo...

In various statistical model, such as density estimation and estimation of regression curves or hazard rates, monotonicity constraints can arise naturally. A frequently encountered problem in nonparametric statistics is to estimate a monotone density function f on a compact interval. A known estimator for density function of f under the restriction that f is decreasing, is Grenander estimator, ...

kernel density estimators are the basic tools for density estimation in non-parametric statistics.  the k-nearest neighbor kernel estimators represent a special form of kernel density estimators, in  which  the  bandwidth  is varied depending on the location of the sample points. in this paper‎, we  initially introduce the k-nearest neighbor kernel density estimator in the random left-truncatio...

fuel cells belong to an avant-garde technology family for a wide variety of applications including micro-power, transportation power, stationary power for buildings and other distributed generation applications. the first objective of this contribution is to find a suitable reduced model of a solid oxide fuel cell (sofc). the derived reduced model is then used to design a state estimator. in th...

The paper presents the combined ridge-stein estimator (CRS) for linear pushbroom imagery exterior orientation, which is severely ill-conditioned for the strong correlation among exterior orientation elements of linear pushbroom imagery. The estimator is a new biased method combining the ridge estimator and the stein estimator. It can effectively change the ill-conditioned state of linear pushbr...

For linear dynamic systems with white process and measurement noise, the Kalman ̄lter is known to be the minimum variance linear state estimator. In the case that the random quantities are Gaussian, then the Kalman ̄lter is the minimim variance state estimator. However, in the application of Kalman ̄lters known signal information is often either ignored or dealt with heuristically. For instance...

in statistical inference, the point estimation problem is very crucial and has a wide range of applications. when, we deal with some concepts such as random variables, the parameters of interest and estimates may be reported/observed as imprecise. therefore, the theory of fuzzy sets plays an important role in formulating such situations. in this paper, we rst recall the crisp uniformly minimum ...

The influence of the global average signal (GAS) on functional-magnetic resonance imaging (fMRI)-based resting-state functional connectivity is a matter of ongoing debate. The global average fluctuations increase the correlation between functional systems beyond the correlation that reflects their specific functional connectivity. Hence, removal of the GAS is a common practice for facilitating ...