19 Filtering and State Estimation Our study of estimating parameters from observations has presumed that there are unchanging parameters to be estimated. For many (if not most) applications this is not so: not only are - State observer - Document - PDFSEARCH.IO

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	19 Filtering and State Estimation Our study of estimating parameters from observations has presumed that there are unchanging parameters to be estimated. For many (if not most) applications this is not so: not only are Add to Reading List Document Date: 2014-04-29 10:51:08 Open Document File Size: 172,36 KB Share Result on Facebook Company MIT’s Radiation Laboratory / / IndustryTerm recursive algorithm / nonlinear systems / off-line applications / / Organization MIT / / Person Norbert Wiener / Bt / / Position model for the relationship / / ProgrammingLanguage K / / Technology GPS / recursive algorithm / t-1 / / SocialTag Signal processing Cybernetics Stochastic differential equations Linear filters Robot control Kalman filter State observer Filtering problem Symmetry-preserving filter Estimation theory

19 Filtering and State Estimation Our study of estimating parameters from observations has presumed that there are unchanging parameters to be estimated. For many (if not most) applications this is not so: not only are Add to Reading List