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— Due to its high compression efficiency, the H.264 video coder is very sensitive to impairments due to transmission over noisy channels. Most error resilience/concealment techniques provided in the H.264 standard were dealing with packet losses. In wireless environments, the proportion of corrupted packets (and thus considered as lost) may become very(More)
In this paper, a new still image coding scheme is presented. In contrast with standard tandem coding schemes, where the redundancy is introduced after source coding, it is introduced before source coding using real BCH codes. A joint channel model is first presented. The model corresponds to a memoryless mixture of Gaussian and Bernoulli-Gaussian noise. It(More)
— Estimating the configuration of a vehicle is crucial for navigation. The most classical approaches are Kalman filtering and Bayesian localization, often implemented via particle filtering. This paper reports ongoing experimentation with an attractive alternative approach recently developed and based on interval analysis. Contrary to classical Extended(More)
This paper is about state estimation for continuous-time nonlinear models, in a context where all uncertain variables can be bounded. More precisely, cooperative models are considered, i.e., models that satisfy some constraints on the signs of the entries of the Jacobian of their dynamic equation. In this context, interval observers and a guaranteed(More)
—When reliable prior bounds on the acceptable errors between the data and corresponding model outputs are available, bounded-error estimation techniques make it possible to characterize the set of all acceptable parameter vectors in a guaranteed way, even when the model is nonlinear and the number of data points small. However, when the data may contain(More)
— We consider continuous-time linear systems with additive disturbances and discrete-time measurements. First, we construct an observer, which converges to the state trajectory of the linear system when the maximum time interval between two consecutive measurements is sufficiently small and there are no disturbances. Second, we construct interval observers(More)
This paper proposes a guaranteed robust bounded-error distributed estimation algorithm. It may be employed to perform parameter estimation from data collected in a network of wireless sensors. The algorithm is robust to an arbitrary number of outliers. Using interval analysis, one is able, provided that the network is connected, to evaluate at each sensor,(More)