Estimating distributions over large alphabets is a fundamental machine-learning tenet. Yet no method is known to estimate all distributions well. For example, add-constant estimators are nearly min-max optimal but often perform poorly in practice, and practical estimators such as absolute discounting, Jelinek-Mercer, and Good-Turing are not known to be near optimal for essentially any distribut...

Good estimates of local mean signal power level are needed by wireless cellular systems for use in channel access, power control and handoff. Many systems today use weighted sample average estimators which are not optimal in Rayleigh fading environments. The optimal local mean signal level estimator for the Rayleigh fading environment will be derived and compared with the sample average estimator.

Linear minimum mean square error (LMMSE) is the optimal channel estimator in (MSE) perspective, however, it requires matrix inversion with cubic complexity. In this paper, by exploiting circulant property of frequency autocorrelation RHH, an efficient LMMSE estimation method has been proposed for orthogonal division multiplexing (OFDM) based on fast Fourier transformation (FFT) and circular con...

This paper investigates a channel estimator based on Gaussian mixture models (GMMs) in the context of linear inverse problems with additive noise. We fit GMM to given samples obtain an analytic probability density function (PDF) which approximates true PDF. Then, conditional mean (CME) corresponding this approximating PDF is computed closed form and used as approximation optimal CME cannot be c...

A relationship between well-known estimator-correlator results from detection theory and the detection of signals in spherically invariant random noise is described. This relationship gives a general result concerning the structure of the likelihood ratio for this detection problem. Furthermore, an alternate formulation of both the likelihood ratio and the optimal estimator that arises in the e...

A Simple GMM Estimator for the Semi-Parametric Mixed Proportional Hazard Model Ridder and Woutersen (2003) have shown that under a weak condition on the baseline hazard there exist root-N consistent estimators of the parameters in a semiparametric Mixed Proportional Hazard model with a parametric baseline hazard and unspecified distribution of the unobserved heterogeneity. We extend the Linear ...