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標(biāo)題: Titlebook: Nonlinear Filtering; Methods and Applicat Kumar Pakki Bharani Chandra,Da-Wei Gu Book 2019 Springer Nature Switzerland AG 2019 Advanced Stat [打印本頁]

作者: Holter-monitor    時(shí)間: 2025-3-21 19:07
書目名稱Nonlinear Filtering影響因子(影響力)




書目名稱Nonlinear Filtering影響因子(影響力)學(xué)科排名




書目名稱Nonlinear Filtering網(wǎng)絡(luò)公開度




書目名稱Nonlinear Filtering網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Nonlinear Filtering被引頻次




書目名稱Nonlinear Filtering被引頻次學(xué)科排名




書目名稱Nonlinear Filtering年度引用




書目名稱Nonlinear Filtering年度引用學(xué)科排名




書目名稱Nonlinear Filtering讀者反饋




書目名稱Nonlinear Filtering讀者反饋學(xué)科排名





作者: 和平主義者    時(shí)間: 2025-3-21 22:11
Kumar Pakki Bharani Chandra,Da-Wei GuIllustrates the complete process of filtering-algorithm derivation.Demonstrates the real-world applications of filtering methods using case studies.MATLAB? codes facilitate the use and adaptation of t
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https://doi.org/10.1007/978-3-030-01797-2Advanced State Estimators; Jacobian-free State Estimation; Numerical Exploration of Filtering Algorith
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Springer Nature Switzerland AG 2019
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作者: 銀版照相    時(shí)間: 2025-3-23 00:10
State Observation and Estimation,rements). If the signal and noise spectra are essentially non-overlapping, the design of a frequency domain filter that allows the desired signal to pass while attenuating the unwanted noise would be a possibility. A classical filter could be either low pass, band pass/stop or high pass. However, wh
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Variants of Cubature Kalman Filter,apter, variants of CKF, namely the cubature information filter (CIF), cubature . filter (C.F) and cubature . information filter (C.IF), and their square-root versions, will be explored. Each of these filters is suitable for particular applications. For example, the CIF is suitable for state estimati
作者: Filibuster    時(shí)間: 2025-3-23 17:21
More Estimation Methods and Beyond,bserver. Though the UKF filter and SDRE observer are based on different philosophies, both of them are derivative-free, nonlinear, state estimators. Their formulations and applications to nonlinear systems are described in this chapter with illustrative application examples. Towards the end of this
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作者: neoplasm    時(shí)間: 2025-3-23 22:27
Jacobian-Based Nonlinear State Estimation,ement dynamics. The idea is, in some key steps of estimation, to replace the nonlinear process and/or measurement models with their corresponding Jacobians. The three filters to be discussed in this chapter are therefore the extended Kalman filter (EKF), extended information filter (EIF) and extended . filter (E.F).
作者: Aggressive    時(shí)間: 2025-3-24 02:47
More Estimation Methods and Beyond,observation data missing occurring in the state estimation will be discussed. The method of linear prediction (LP) is particularly introduced to alleviate the adverse effect of data missing in the state estimation, together with a numerical example.
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nonlinear control systems analysis and design.?The chief features of the book include: dedicated coverage of recently developed nonlinear, Jacobian-free, filtering algorithms; examples illustrating the use of n978-3-030-01797-2
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