Mehdi Chitchian

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We present the design, analysis, and real-time implementation of a distributed computation particle filter on a graphic processing unit (GPU) architecture that is especially suited for fast real-time control applications. The proposed filter architecture is composed of a number of local subfilters that can share limited information among each other via an(More)
The particle filter is a Bayesian estimation technique based on Monte Carlo simulation. The nonparametric nature of particle filters makes them ideal for non-linear, non-Gaussian dynamic systems. Particle filtering has many applications: in computer vision, robotics, and econometrics to name just a few. Although superior to Kalman filters, particle filters(More)
The particle filter is a Bayesian estimation technique based on Monte Carlo simulation. It is ideal for non-linear, nonGaussian dynamical systems with applications in many areas, such as computer vision, robotics, and econometrics. Practical use has so far been limited, because of steep computational requirements. In this study, we investigate how to design(More)
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