Recently, the field of machine translation has increasingly reflected the influence of linguistic theory. Some systems have been designed around principles or structures of specific theories (Dorr, 1989; Kaplan, Netter, Wedekind, & Zaenen, 1989; Sharp, 1986), whereas others, adhering less strongly to particular theories, nevertheless reflect great care in considering and adapting the work of li...

The strategy and financial economics literature have long investigated the problem of adverse selection between buyers and sellers in M&A markets, which can create inefficiencies and stop acquirers from gaining access to valuable resources and capabilities via acquisitions. In turn, the entrepreneurship literature has highlighted the challenges faced by entrepreneurial firms to raise external c...

state estimation is the foundation of any control and decision making in power networks. the first requirement for a secure network is a precise and safe state estimator in order to make decisions based on accurate knowledge of the network status. this paper introduces a new estimator which is able to detect bad data with few calculations without need for repetitions and estimation residual cal...

Let be a random sample from a normal distribution with unknown mean and known variance The usual estimator of the mean, i.e., sample mean is the maximum likelihood estimator which under squared error loss function is minimax and admissible estimator. In many practical situations, is known in advance to lie in an interval, say for some In this case, the maximum likelihood estimator...

Correlation dimension is attained from the correlations between random points on the attractor. For an one dimensional discrete dynamical system with initial condition, x0 Lyapunov exponent (x0) is defined. The Henon map is a discrete time dynamical system. In logistic map is quadratic. The Kaplan-Yorke map is a discrete -time dynamical system. A nnr ( ) subroutine is written to find all mean n...

Constructing a fast and efficient estimator for the B-mode power spectrum of cosmic microwave background (CMB) is critical importance CMB science. For general survey, Quadratic Maximum Likelihood (QML) polarization has been proved to be optimal with minimal uncertainties, but it computationally very expensive. In this article, we propose two new QML methods estimation. We use Smith–Zaldarriaga ...

In this paper we present an MMSE (minimum mean square error) speech feature enhancement algorithm, capitalizing on a new probabilistic, nonlinear environment model that effectively incorporates the phase relationship between the clean speech and the corrupting noise in acoustic distortion. The MMSE estimator based on this phase-sensitive model is derived and it achieves high efficiency by explo...

This paper proposes a motion estimation algorithm that is robust to motion discontinuity and noise. The proposed algorithm is constructed by embedding the least median squares (LMedS) of robust statistics into the maximum a posteriori (MAP) estimator. Difficulties in accurate estimation of the motion field arise from the smoothness constraint and the sensitivity to noise. To cope robustly with ...

Abstract The objective of this work is the super-resolution enhancement of image sequences. We consider in particular images of scenes for which the point-to-point image transformation is a plane projective transformation. We first describe the imaging model, and a maximum likelihood (ML) estimator of the super-resolution image. We demonstrate the extreme noise sensitivity of the unconstrained ...

This paper addresses the joint path delay and time-varying complex gain estimation for continuous phase modulation (CPM), over a time-selective slowly varying Rayleigh flat fading channel. We propose two estimation methods: an expectation-maximization (EM) algorithm for path delay estimation in a Kalman framework, and a Maximum a Posteriori (MAP) method for joint path delay and complex gain est...