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- W2950544563 abstract "This paper considers the problem of state tracking with observation control for a particular class of dynamical systems. The system state evolution is described by a discrete-time, finite-state Markov chain, while the measurement process is characterized by a controlled multi-variate Gaussian observation model. The computational complexity of the optimal control strategy proposed in our prior work proves to be prohibitive. A suboptimal, lower complexity algorithm based on the Fisher information measure is proposed. Toward this end, the preceding measure is generalized to account for multi-valued discrete parameters and control inputs. A closed-form formula for our system model is also derived. Numerical simulations are provided for a physical activity tracking application showing the near-optimal performance of the proposed algorithm." @default.
- W2950544563 created "2019-06-27" @default.
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- W2950544563 date "2014-08-19" @default.
- W2950544563 modified "2023-10-18" @default.
- W2950544563 title "Controlled Sensing: A Myopic Fisher Information Sensor Selection Algorithm" @default.
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