We detail in this paper the implementation of the optimal Bayes multiframe detector/tracker for rigid objects moving randomly in two-dimensional (2D) finite grids. We present 2D models for target signature and target motion that build an integrated framework for detection and tracking. We model the background clutter by 2D correlated noncausal Gauss-Markov fields of arbitrary order. By explorin...

Abstract Cognitive radio (CR) is designed to implement dynamical spectrum sharing and reduce the negative effect of scarcity caused by exponential increase in number wireless devices. CR requires that sensing should detect licenced signals quickly accurately enable coexistence between primary secondary users without interference. However, with a low signal-to-noise ratio (SNR) still challenge s...

Nowadays, empty speech pause detection algorithms play an important role in several speech processing fields such as speech recognition, speech enhancement, and speech coding. This work describes two new pause detection algorithms and compare their performance with four standard Voice Activity Detection (VAD) methods represented by the adaptive Long Term Spectral Divergence (LTSD) algorithm, th...

This paper shows a revised statistical test for voice activity detection in noise adverse environments. The method is based on a revised contextual likelihood ratio test (LRT) defined over a multiple observation window. The new approach not only evaluates the two hypothesis consisting on all the observations to be speech or non-speech but all the possible hypothesis defined over the individual ...

This paper considers the problem of speci cation testing in general parametric models and shows that for a wide class of models the hypothesis of correct speci cation is equivalent to a continuum of moment equalities. Using these moment equalities we construct a class of speci cation tests that have correct asymptotic size in general parametric models, including stationary time series models, a...

A generalized likelihood ratio test is considered for testing acoustic propagation models in the context of environmental parameter inversion. In the following, we use the term \hierarchy of models" to denote a sequence of model structures M1;M2;... in which each particular model structure Mn contains all previous ones as special cases. We propose a combined parameter estimation and multiple se...

This paper proposes a modified quasi-likelihood test of Markov regime switching models. Despite its popularity in economics and finance, there are few papers that develop tests for regime switching models. Recently, Cho and White (2007) derive the asymptotic distribution of the quasi-likelihood ratio (QLR) statistic of Markov regime switching models with a scalar parameter. The asymptotic distr...

These integrations can sometimes be performed analytically, or using some numerical integration techniques. However, we will focus instead on a simple heuristic method which is related to the χ statistics discussed above. Note that David MacKay [3] explicitly assumes the parameters have an ’intrinsic’ arity to them (multinomials with an intrinsic number of bins). This assumption may not be alwa...

We evaluate by simulation three model-based methods to test the influence of a single nucleotide polymorphism on a pharmacokinetic parameter of a drug: analysis of variance (ANOVA) on the empirical Bayes estimates of the individual parameters, likelihood ratio test between models with and without genetic covariate, and Wald tests on the parameters of the model with covariate. Analyses are perfo...

The empirical likelihood ratio (ELR) test for the problem of testing for normality is derived in this paper. The sampling properties of the ELR test and four other commonly used tests are provided and analyzed using the Monte Carlo simulation technique. The power comparisons against a wide range of alternative distributions show that the ELR test is the most powerful of these tests in certain s...