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- W2358561170 abstract "Since likely model set(LMS) algorithm can't guarantee that model set adaptation is done correctly and timely,errors may be introduced in the target state estimate.If LMS go back n-step in time to initialize the newly activated models,the state esti-mate error will be reduced in some degree.But this method also increases the computation complexity.Some different N-step back LMS algorithms are compared.Simulation results indicate that LMS go back one or two steps can improve the precision of the state estimate,especially when the model set used is small." @default.
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- W2358561170 date "2010-01-01" @default.
- W2358561170 modified "2023-09-24" @default.
- W2358561170 title "A Comparative Study on N-step Back Likely-model Set Algorithm" @default.
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