Introduces a DUIO framework that combines local state reconstruction with distributed optimization to achieve bounded-error estimation in discrete-time systems with unknown inputs.
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Derives explicit formula for causally conditioned directed information rate of Gaussian sequences based on optimal prediction and proves O(N^{-1/2} log N) high-probability error bound for the resulting estimator.
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Distributed State Estimation for Discrete-Time Systems With Unknown Inputs: An Optimization Approach
Introduces a DUIO framework that combines local state reconstruction with distributed optimization to achieve bounded-error estimation in discrete-time systems with unknown inputs.