It is proposed to jointly estimate the parameters of nonGaussian autoregressive (AR) processes in a Bayesian context using the Gibbs sampler. Using the Markov chains produced by the sampler an approximation to the vector MAP estimator is implemented. The results reported here used AR(4) models driven by noise sequences where each sample is iid as a two component Gaussian sum mixture. The result...

In this article, we present an approach towards a new nonintrusive speech quality estimator. The proposed method facilitates the evaluation of speech telephony services and provides diagnostic information by assessing dimensions of the perceptual quality space. One of these quality dimensions is Loudness, which describes a non optimal sound level. As an important part of the proposed model, a n...

In this paper, we develop a recursive model-based maximum a posteriori (MAP) estimator that simultaneously e& timates the displacement vector field (DVF) and intensity field from a noisy-blurred image sequence. Current motioncompensated spatio-temporal filters treat the estimation of the DVF as a preprocessing step. Thereby, no attempt is made to verify the accuracy of these estimates prior to ...

The problem of joint oscillator phase noise (PHN) estimation and data detection for multi-input multi-output (MIMO) systems using bit-interleaved-coded modulation is analysed. A new MIMO receiver that iterates between the estimator and the detector, based on the expectation-maximisation (EM) framework, is proposed. It is shown that at high signal-to-noise ratios, a maximum a posteriori (MAP) es...

This work is concerned with tracking and system identification for time-varying parameters. The parameters areMarkov chains and the observations are binary valuedwith noise corruption. To overcome the difficulties due to the limited measurement information, Wonham-type filters are developed first. Then, based on the filters, two popular estimators, namely, mean squares estimator (MSQ) andmaximu...

In this paper we address sequence estimation when the InterSymbol Interference (ISI) communication channel is unknown and time varying. We employ a Maximum A Posterior (MAP) approach, in which the unknown channel parameters are assigned a distribution and integrated out. For several channel models of interest we describe both the exact MAP estimator and Viterbi algorithm based implementations. ...

We thank Vansteelandt and Keiding (1) for their commentary on our article (2), in which we implemented G-computation, a maximum likelihood-based substitution estimator of the G-formula. The goals of that article included 1) translating G-computation into the applied epidemiology literature by using a point-treatment example and marginal parameter, 2) drawing connections between traditional regr...

During digital video acquisition, imagery may be degraded by a number of phenomena including undersampling, blur, and noise. Many systems, particularly those containing infrared focal plane array (FPA) sensors, are also subject to detector nonuniformity. Nonuniformity, or fixed pattern noise, results from nonuniform responsivity of the photodetectors that make up the FPA. Here we propose a maxi...

The properties of the Cosmic Microwave Background (CMB) maps carry valuable cosmological information. Here we report the results of the analysis of ellipticity of the hot and cold CMB anisotropy spots in the BOOMERanG 150 GHz map. We carried out this analysis for the map obtained by summing independent measurement channels (signal plus noise map) and for a comparison map (noise only map) obtain...