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Differentiable interacting multiple model particle filtering
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DOI：10.1016/j.sigpro.2025.110166.png)
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Abstract
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• This paper addresses the issue of parameter learning in state-space systems with behaviour jumps (or regime switching). • We propose the first filter that can learn the switching process and underlying models simultaneously. • The new filter performs better than the previous (non-filtering) state-of-the-art.
Keywords:
62M20
62F12
Sequential Monte Carlo
Differentiable particle filtering
Regime switching
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