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This paper discusses a result for error control techniques based on retransmissions, most notably hybrid automatic repeat request schemes. We assume that the underlying coding technique is described by the so-called reliable region. Under this assumption, we derive the channel distribution after a frame is either acknowledged or discarded. This is derived within an entirely analytical framework, where...
This paper presents despeckling and information extraction using non-quadratic regularization. The novelty of this paper is that instead of the Gaussian prior model a Gauss-Markov random field model is chosen, because it can efficiently model textures in the images. The iterative procedure consists of noise-free image and texture parameter. The experimental results show that the proposed method satisfactorily...
From the Bayesian statistical inference theory, a new mixed spectrum estimation method, which is based on Markov chain Monte Carlo (MCMC) approach, is proposed in this paper. The proposed method iteratively extracts the estimates of sinusoid parameters via the traditional methods, and estimates the ones of AR clutter parameters via the MCMC approach. Because the MCMC approach can fully dig the inherent...
In this paper we present a Markovian method of classification of the satellite images, this method is based on a minimization of the posterior energy by the ICM method (iterated conditional mode) with the introduction of constraints of the spatial context. The originality of our method is the variability over the iterations of a temperature factor like in the simulated annealing algorithm (SA), indeed,...
An analytic model is proposed to assess the performance of optimistic software transactional memory (STM) systems with in-place memory updates for write operations. Based on an absorbing discrete-time Markov chain, closed-form analytic expressions are developed, which are quickly solved iteratively to determine key parameters of the STM system. The model covers complex implementation details such...
In this paper, we investigate the design of low-density parity-check (LDPC) codes for the Gilbert-Elliott (GE) channel. Recently, Eckford et al. proposed a design method of irregular LDPC codes using approximate density-evolution (DE) for Markov channels. In the design method proposed by Eckford et al., the probability density function (PDF) of the messages from variable nodes to check nodes is approximated...
This paper presents a distributed sensor localization algorithm with inter-sensor distance information in m-dimensional Euclidean space using only m + 1 anchors (sensors that know their exact locations). Under the assumption that the M sensors (with unknown locations) lie in the convex hull of the m + 1 anchors and the underlying network is connected, we derive a linear algorithm that employs barycentric...
A partial ordering on general finite-state Markov channels is given, which orders the channels in terms of probability of symbol error under iterative estimation decoding of a low-density parity-check (LDPC) code. This result is intended to mitigate the complexity of characterizing the performance of general finite-state Markov channels, which is difficult due to the large parameter space of this...
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