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We study systems of particle filters that track targets based on data acquired from a network of sensors. We build on our previous concept of symbiotic particle filtering and propose a system of particle filters, where each one of them explores a state space of minimal dimension. The number of particle filters in the system varies in that more particle filters may be added to the system, some may...
In this paper, we propose a model for proliferation of cancer stem cells and a procedure for estimating the unknowns of the model. Understanding the proliferation of cancer stem cells is critical for the development of anti-cancer therapies. We propose to use a nonlinear and non-Gaussian state-space model for studying the proliferation process. For estimation of the unknowns we apply particle filtering,...
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