Particle filters are used to effectively compute the expectation of complex functionals of a stochastic process, e.g. when filtering a signal from noisy observations. These algorithms are a priori not parallelizable (though there have been such attempts). We present a modification which could run on a rectangular processor array and, using parallelism and local communication, computes these filters quickly and accurately (as test runs indicate).
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