PROJECT TITLE :
Recursive Hybrid Cramér–Rao Bound for Discrete-Time Markovian Dynamic Systems
In statistical Signal Processing, hybrid parameter estimation refers back to the case where the parameters vector to estimate contains both non-random and random parameters. As a contribution to the hybrid estimation framework, we have a tendency to introduce a recursive hybrid Cramér–Rao lower certain for discrete-time Markovian dynamic systems depending on unknown deterministic parameters. Additionally, the regularity conditions required for its existence and its use are clarified.
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