Michele Pace

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M. Riedel∗,†, E. Laure, Th. Soddemann, L. Field, J. P. Navarro, J. Casey,M. Litmaath, J. Ph. Baud, B. Koblitz, C. Catlett, D. Skow,C. Zheng, P. M. Papadopoulos,M. Katz, N. Sharma, O. Smirnova, B. Kónya, P. Arzberger, F. Würthwein, A. S. Rana, T. Martin,M. Wan,V. Welch, T. Rimovsky, S. Newhouse, A. Vanni, Y. Tanaka, Y. Tanimura, T. Ikegami, D. Abramson, C.(More)
Tracing resource usage by Grid users is of utmost importance especially in the context of large-scale scientific collaborations such as within the High Energy Physics (HEP) community to guarantee fairness of resource sharing, but many difficulties can arise when tracing the resource usage of distributed applications over heterogeneous Grid platforms. These(More)
The Probability Hypothesis Density (PHD) filter is applied to realistic three-dimensional aerial and naval scenarios to illustrate its performance in detecting, initiating and terminating tracks in presence of clutter. Radar measurements are available every two seconds. A comparisons between different approximations of the PHD recursion, namely the(More)
We analyse the exponential stability properties of a class of measure-valued equations arising in nonlinear multi-target filtering problems. We also prove the uniform convergence properties w.r.t. the time parameter of a rather general class of stochastic filtering algorithms, including sequential Monte Carlo type models and mean field particle(More)
We discuss a connection between spatial branching processes and the PHD recursion based on conditioning principles for Poisson Point Processes. The branching process formulation gives a generalized Feynman-Kac systems interpretation of the PHD filtering equations, which enables the derivation of mean-field implementations of the PHD filter. This approach(More)
We design a mean field and interacting particle interpretation of a class of spatial branching intensity models with spontaneous births arising in multiple-target tracking problems. In contrast to traditional Feynman-Kac type particle models, the transitions of these interacting particle systems depend on the current particle approximation of the total mass(More)
We propose an approach to calculate the Probability Hypothesis Density function on a numerical grid by using a method based on the convolution theorem and Fast Fourier transform. This approach provides a representation of the PHD over a discretized domain and, unlike other techniques, does not require Gaussian assumptions on the target and observation(More)
  • Michele Pace
  • 2009 IEEE Symposium on Computational Intelligence…
  • 2009
In game theory, the Traveler's Dilemma (abbreviated TD) is a non-zero-sum <sup>1</sup> game in which two players attempt to maximize their own payoff without deliberately willing to damage the opponent. In the classical formulation of this problem, game theory predicts that, if both players are purely rational, they will always choose the strategy(More)
The aim of this paper is two-fold. First we analyze the sequence of intensity measures of a spatial branching point process arising in a multiple target tracking context. We study its stability properties, characterize its long time behavior and provide a series of weak Lipschitz type functional contraction inequalities. Second we design and analyze an(More)
The Probability Hypothesis Filter, which propagates the first moment, or intensity function, of a point process has become more and more popular to address multi-tracking problems. Under linear-Gaussian assumptions, the intensity function takes the form of a mixture of Gaussian kernels. As the number of elements increases exponentially over time,(More)