7173903Extended Kalman Filterhttps://www.gandhi.com.mx/extended-kalman-filter-6610000683321/phttps://gandhi.vtexassets.com/arquivos/ids/6714581/image.jpg?v=6386982937597700006969MXNOne Billion KnowledgeableInStock/Ebooks/6829260Extended Kalman Filter6969https://www.gandhi.com.mx/extended-kalman-filter-6610000683321/phttps://gandhi.vtexassets.com/arquivos/ids/6714581/image.jpg?v=638698293759770000InStockMXN99999DIEbook20246610000683321_W3siaWQiOiJkMjBiNTZiOC1lOThlLTQ5NGYtYWY4Ny0wZTkzODUzMmU5NDAiLCJsaXN0UHJpY2UiOjk5LCJkaXNjb3VudCI6MCwic2VsbGluZ1ByaWNlIjo5OSwiaW5jbHVkZXNUYXgiOnRydWUsInByaWNlVHlwZSI6IklwcCIsImN1cnJlbmN5IjoiTVhOIiwiZnJvbSI6IjIwMjQtMTItMTVUMDA6MDA6MDBaIiwicmVnaW9uIjoiTVgiLCJpc1ByZW9yZGVyIjpmYWxzZX1d6610000683321_1: Extended Kalman filter: Introduces the extended Kalman filter (EKF), a core tool in nonlinear estimation.2: Braket notation: Explains the mathematical foundation, focusing on the structure of quantumlike systems.3: Curvature: Discusses the concept of curvature and its influence on the performance of nonlinear filters.4: Maximum likelihood estimation: Details the statistical approach used for estimating parameters with the highest likelihood.5: Kalman filter: Provides an indepth exploration of the Kalman filter, the basis for many state estimation techniques.6: Covariance matrix: Describes the covariance matrix and its role in quantifying uncertainty in filtering.7: Propagation of uncertainty: Explores how uncertainty propagates over time and affects filtering accuracy.8: LevenbergMarquardt algorithm: Introduces this algorithm, which optimizes nonlinear least squares problems.9: Confidence region: Explains the statistical region that quantifies the precision of parameter estimates.10: Nonlinear regression: Focuses on methods for fitting nonlinear models to data using optimization techniques.11: Estimation theory: Provides the theory behind estimation, essential for understanding filter design and analysis.12: Generalized least squares: Discusses the generalized approach for solving regression problems in the presence of heteroscedasticity.13: Von MisesFisher distribution: Introduces this probability distribution useful for directional data in high dimensions.14: Ensemble Kalman filter: Explores a variation of the Kalman filter suitable for largescale nonlinear systems.15: Filtering problem (stochastic processes): Details how filtering can be applied to random processes in dynamic systems.16: GPS/INS: Describes the integration of GPS and inertial navigation systems for precise navigation and estimation.17: Linear least squares: Covers the least squares method for solving linear regression problems.18: Symmetrypreserving filter: Introduces filters designed to preserve symmetry in systems, important in robotics.19: Invariant extended Kalman filter: Explains a variation of EKF that maintains invariance in nonlinear systems.20: Unscented transform: Discusses the unscented transform, a technique for improving state estimation in nonlinear models.21: SAMV (algorithm): Introduces the SAMV algorithm for robust estimation in uncertain environments....6610000683321_One Billion Knowledgeablelibro_electonico_6610000683321_6610000683321Fouad SabryInglésMéxicohttps://getbook.kobo.com/koboid-prod-public/content2connect_drm-epub-4ed84639-c6fe-41e2-a2d4-96305b455126.epub2024-12-13T00:00:00+00:00One Billion Knowledgeable