An innovation approach to the smoothing problem from uncertain observations with correlated signal and noise
Copyright policy )An innovation approach to the smoothing problem from uncertain observations with correlated signal and noise
Summary: This paper treats the least mean-squared error linear fixed-point and fixed-lag smoothing problems from uncertain observations, when the variables describing the uncertainty are independent, and the signal and observation white noise are correlated. Using an innovation approach, recursive algorithms are derived for both estimators without requiring the whole knowledge of the state-space model generating the signal, but only covariance information of the signal and the observation noise, as well as the probability that the signal exists in the observed values.
- University of Granada Spain
- Kagoshima University Japan
- University of Jaén Spain
Signal theory (characterization, reconstruction, filtering, etc.), innovation process, Data smoothing in stochastic control theory, fixed-lag smoothing, covariance information, uncertain observations, Statistical aspects of information-theoretic topics, Inference from stochastic processes and prediction, Filtering in stochastic control theory, Least squares and related methods for stochastic control systems, Signal detection and filtering (aspects of stochastic processes), fixed-point smoothing
Signal theory (characterization, reconstruction, filtering, etc.), innovation process, Data smoothing in stochastic control theory, fixed-lag smoothing, covariance information, uncertain observations, Statistical aspects of information-theoretic topics, Inference from stochastic processes and prediction, Filtering in stochastic control theory, Least squares and related methods for stochastic control systems, Signal detection and filtering (aspects of stochastic processes), fixed-point smoothing
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