Khác biệt giữa bản sửa đổi của “Bộ lọc Kalman”
Nội dung được xóa Nội dung được thêm vào
Dòng 4: | Dòng 4: | ||
==Tham khảo== |
==Tham khảo== |
||
{{tham khảo}} |
{{tham khảo}} |
||
==Nghiên cứu thêm== |
|||
== Further reading == |
|||
{{refbegin|30em}} |
|||
* {{ cite book | author = Einicke, G.A. | year = 2012 | title = Smoothing, Filtering and Prediction: Estimating the Past, Present and Future | publisher = Intech | location = Rijeka, Croatia | isbn = 978-953-307-752-9 | url = http://www.intechopen.com/books/smoothing-filtering-and-prediction-estimating-the-past-present-and-future}} |
|||
* {{ cite book | author = Gelb, A. | year = 1974 | title = Applied Optimal Estimation | publisher = MIT Press | isbn = }} |
|||
* {{ cite journal | author = Kalman, R.E. | year = 1960 | title = A new approach to linear filtering and prediction problems | journal = Journal of Basic Engineering | volume = 82 | issue = 1 | pages = 35–45 | url = http://www.elo.utfsm.cl/~ipd481/Papers%20varios/kalman1960.pdf | accessdate = 2008-05-03 }} |
|||
* {{ cite journal | author = Kalman, R.E. | coauthors = Bucy, R.S. | year = 1961 | title = New Results in Linear Filtering and Prediction Theory | url = http://www.dtic.mil/srch/doc?collection=t2&id=ADD518892|verb=getRecord&metadataPrefix=html&identifier=ADD518892 | accessdate = 2008-05-03 }} |
|||
* {{ cite book | author = Harvey, A.C. | year = 1990 | title = Forecasting, Structural Time Series Models and the Kalman Filter | publisher = Cambridge University Press | isbn = }} |
|||
* {{ cite journal | author = Roweis, S. | coauthors = Ghahramani, Z. | year = 1999 | title = A Unifying Review of Linear Gaussian Models | journal = Neural Computation | volume = 11 | issue = 2 | pages = 305–345 | doi = 10.1162/089976699300016674 | pmid = 9950734 }} |
|||
* {{ cite book | author = Simon, D. | year = 2006 | title = Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches | publisher = Wiley-Interscience | url = http://academic.csuohio.edu/simond/estimation/ | isbn = }} |
|||
* {{ cite book | author = Stengel, R.F. | year = 1994 | title = Optimal Control and Estimation | publisher = Dover Publications | isbn = 0-486-68200-5 | url = http://www.princeton.edu/~stengel/OptConEst.html }} |
|||
* {{ cite journal | author = [[Kevin Warwick|Warwick, K]]. | year = 1987 | title = Optimal observers for ARMA models | journal = International Journal of Control | volume = 46 | issue = 5 | pages = 1493–1503 | url = http://www.informaworld.com/index/779885789.pdf | accessdate = 2008-05-03 | doi = 10.1080/00207178708933989 }} |
|||
* {{ cite book | author = Bierman, G.J. | year = 1977 | title = Factorization Methods for Discrete Sequential Estimation | journal = Mathematics in Science and Engineering | volume = 128 | isbn = 978-0-486-44981-4 | publisher = Dover Publications | location = Mineola, N.Y. }} |
|||
* {{ cite book | author = Bozic, S.M. | year = 1994 | title = Digital and Kalman filtering | publisher = Butterworth-Heinemann | isbn = }} |
|||
* {{ cite book | author = Haykin, S. | year = 2002 | title = Adaptive Filter Theory | publisher = Prentice Hall | isbn = }} |
|||
* {{ cite book | author = Liu, W. | coauthors = Principe, J.C. and Haykin, S. | year = 2010 | title = Kernel Adaptive Filtering: A Comprehensive Introduction | publisher = John Wiley | isbn = }} |
|||
* {{ cite book | author = Manolakis, D.G. | year = 1999 | title = Statistical and Adaptive signal processing | publisher = Artech House | isbn = }} |
|||
* {{ cite journal | author = Welch, Greg | coauthors = Bishop, Gary | year = 1997 | title = SCAAT: Incremental Tracking with Incomplete Information | url = http://www.cs.unc.edu/~welch/media/pdf/scaat.pdf | pages = 333–344 | isbn = 0-89791-896-7 | doi = 10.1145/258734.258876 | publisher = ACM Press/Addison-Wesley Publishing Co }} |
|||
* {{ cite book | first=Andrew H. |last= Jazwinski | year = 1970 | title = Stochastic Processes and Filtering | publisher = [[Academic Press]] | location=New York | series = Mathematics in Science and Engineering | pages=376 | isbn=0-12-381550-9 }} |
|||
* {{ cite book | first=Peter S. |last=Maybeck | year = 1979 | title = Stochastic Models, Estimation, and Control | publisher = [[Academic Press]] | location=New York | isbn = 0-12-480701-1 | volume = 141-1 | series = Mathematics in Science and Engineering | pages=423 }} |
|||
* {{ cite book | author = Moriya, N. | year = 2011 | title = Primer to Kalman Filtering: A Physicist Perspective | publisher = [[Nova Science Publishers, Inc]] | location=New York | isbn = 978-1-61668-311-5 }} |
|||
* {{ cite journal | author = Dunik, J. | coauthors = Simandl M., Straka O. | year = 2009 | title = Methods for estimating state and measurement noise covariance matrices: Aspects and comparisons. | journal = Proceedings of 15th IFAC Symposium on System Identification | place = France | pages = 372–377 }} |
|||
* {{ cite book | first=Charles K. |last=Chui |first2=Guanrong |last2=Chen | year = 2009 | title = Kalman Filtering with Real-Time Applications | publisher = [[Springer Science+Business Media|Springer]] | location=New York | isbn = 978-3-540-87848-3 | volume = 17 | series = Springer Series in Information Sciences | edition = 4th | pages=229 }} |
|||
* {{ cite journal | author = Spivey, Ben | coauthors = Hedengren, J. D. and Edgar, T. F. | journal = Industrial & Engineering Chemistry Research | volume = 49 | issue = 17 | year = 2010 | title = Constrained Nonlinear Estimation for Industrial Process Fouling | url = http://pubs.acs.org/doi/abs/10.1021/ie9018116 | pages = 7824–7831 | doi = 10.1021/ie9018116 }} |
|||
* [[Thomas Kailath]], [[Ali H. Sayed]], and [[Babak Hassibi]], Linear Estimation, Prentice-Hall, NJ, 2000, ISBN 978-0-13-022464-4. |
|||
* [[Ali H. Sayed]], Adaptive Filters, Wiley, NJ, 2008, ISBN 978-0-470-25388-5. |
|||
{{refend}} |
|||
== Liên kết ngoài == |
== Liên kết ngoài == |
||
* [http://www.cs.unc.edu/~welch/kalman/kalmanPaper.html A New Approach to Linear Filtering and Prediction Problems], by R. E. Kalman, 1960 |
* [http://www.cs.unc.edu/~welch/kalman/kalmanPaper.html A New Approach to Linear Filtering and Prediction Problems], by R. E. Kalman, 1960 |
Phiên bản lúc 16:01, ngày 5 tháng 6 năm 2013
Bộ lọc Kalman, được Rudolf (Rudy) E. Kálmán công bố năm 1960, là thuật toán sử dụng chuỗi các giá trị đo lường, bị ảnh hưởng bởi nhiễu hoặc sai số, để ước đoán biến số nhằm tăng độ chính xác so với việc sử dụng duy nhất một giá trị đo lường. Bộ lọc Kalman thực hiện phương pháp truy hồi đối với chuỗi các giá trị đầu vào bị nhiễu, nhằm tối ưu hóa giá trị ước đoán trạng thái của hệ thống.
Tham khảo
Nghiên cứu thêm
Further reading
- Einicke, G.A. (2012). Smoothing, Filtering and Prediction: Estimating the Past, Present and Future. Rijeka, Croatia: Intech. ISBN 978-953-307-752-9.
- Gelb, A. (1974). Applied Optimal Estimation. MIT Press.
- Kalman, R.E. (1960). “A new approach to linear filtering and prediction problems” (PDF). Journal of Basic Engineering. 82 (1): 35–45. Truy cập ngày 3 tháng 5 năm 2008.
- Kalman, R.E. (1961). “New Results in Linear Filtering and Prediction Theory”. Truy cập ngày 3 tháng 5 năm 2008. Đã bỏ qua tham số không rõ
|coauthors=
(gợi ý|author=
) (trợ giúp); Đã bỏ qua tham số không rõ|verb=
(trợ giúp); Chú thích journal cần|journal=
(trợ giúp) - Harvey, A.C. (1990). Forecasting, Structural Time Series Models and the Kalman Filter. Cambridge University Press.
- Roweis, S. (1999). “A Unifying Review of Linear Gaussian Models”. Neural Computation. 11 (2): 305–345. doi:10.1162/089976699300016674. PMID 9950734. Đã bỏ qua tham số không rõ
|coauthors=
(gợi ý|author=
) (trợ giúp) - Simon, D. (2006). Optimal State Estimation: Kalman, H Infinity, and Nonlinear Approaches. Wiley-Interscience.
- Stengel, R.F. (1994). Optimal Control and Estimation. Dover Publications. ISBN 0-486-68200-5.
- Warwick, K. (1987). “Optimal observers for ARMA models” (PDF). International Journal of Control. 46 (5): 1493–1503. doi:10.1080/00207178708933989. Truy cập ngày 3 tháng 5 năm 2008.
- Bierman, G.J. (1977). Factorization Methods for Discrete Sequential Estimation. Mathematics in Science and Engineering. 128. Mineola, N.Y.: Dover Publications. ISBN 978-0-486-44981-4.
- Bozic, S.M. (1994). Digital and Kalman filtering. Butterworth-Heinemann.
- Haykin, S. (2002). Adaptive Filter Theory. Prentice Hall.
- Liu, W. (2010). Kernel Adaptive Filtering: A Comprehensive Introduction. John Wiley. Đã bỏ qua tham số không rõ
|coauthors=
(gợi ý|author=
) (trợ giúp) - Manolakis, D.G. (1999). Statistical and Adaptive signal processing. Artech House.
- Welch, Greg (1997). “SCAAT: Incremental Tracking with Incomplete Information” (PDF). ACM Press/Addison-Wesley Publishing Co: 333–344. doi:10.1145/258734.258876. ISBN 0-89791-896-7. Đã bỏ qua tham số không rõ
|coauthors=
(gợi ý|author=
) (trợ giúp); Chú thích journal cần|journal=
(trợ giúp) - Jazwinski, Andrew H. (1970). Stochastic Processes and Filtering. Mathematics in Science and Engineering. New York: Academic Press. tr. 376. ISBN 0-12-381550-9.
- Maybeck, Peter S. (1979). Stochastic Models, Estimation, and Control. Mathematics in Science and Engineering. 141–1. New York: Academic Press. tr. 423. ISBN 0-12-480701-1.
- Moriya, N. (2011). Primer to Kalman Filtering: A Physicist Perspective. New York: Nova Science Publishers, Inc. ISBN 978-1-61668-311-5.
- Dunik, J. (2009). “Methods for estimating state and measurement noise covariance matrices: Aspects and comparisons”. Proceedings of 15th IFAC Symposium on System Identification. France: 372–377. Đã bỏ qua tham số không rõ
|coauthors=
(gợi ý|author=
) (trợ giúp) - Chui, Charles K.; Chen, Guanrong (2009). Kalman Filtering with Real-Time Applications. Springer Series in Information Sciences. 17 (ấn bản 4). New York: Springer. tr. 229. ISBN 978-3-540-87848-3.
- Spivey, Ben (2010). “Constrained Nonlinear Estimation for Industrial Process Fouling”. Industrial & Engineering Chemistry Research. 49 (17): 7824–7831. doi:10.1021/ie9018116. Đã bỏ qua tham số không rõ
|coauthors=
(gợi ý|author=
) (trợ giúp) - Thomas Kailath, Ali H. Sayed, and Babak Hassibi, Linear Estimation, Prentice-Hall, NJ, 2000, ISBN 978-0-13-022464-4.
- Ali H. Sayed, Adaptive Filters, Wiley, NJ, 2008, ISBN 978-0-470-25388-5.
Liên kết ngoài
- A New Approach to Linear Filtering and Prediction Problems, by R. E. Kalman, 1960
- Kalman–Bucy Filter, a good derivation of the Kalman–Bucy Filter
- MIT Video Lecture on the Kalman filter
- An Introduction to the Kalman Filter, SIGGRAPH 2001 Course, Greg Welch and Gary Bishop
- Kalman filtering chapter from Stochastic Models, Estimation, and Control, vol. 1, by Peter S. Maybeck
- Kalman Filter webpage, with lots of links
- Kalman Filtering
- Kalman Filters, thorough introduction to several types, together with applications to Robot Localization
- Kalman filters used in Weather models, SIAM News, Volume 36, Number 8, October 2003.
- Critical Evaluation of Extended Kalman Filtering and Moving-Horizon Estimation, Ind. Eng. Chem. Res., 44 (8), 2451–2460, 2005.
- Source code for the propeller microprocessor: Well documented source code written for the Parallax propeller processor.
- Gerald J. Bierman's Estimation Subroutine Library: Corresponds to the code in the research monograph "Factorization Methods for Discrete Sequential Estimation" originally published by Academic Press in 1977. Republished by Dover.
- Matlab Toobox implementing parts of Gerald J. Bierman's Estimation Subroutine Library: UD / UDU' and LD / LDL' factorization with associated time and measurement updates making up the Kalman filter.
- Matlab Toolbox of Kalman Filtering applied to Simultaneous Localization and Mapping: Vehicle moving in 1D, 2D and 3D
- Derivation of a 6D EKF solution to Simultaneous Localization and Mapping (In old version PDF). See also the tutorial on implementing a Kalman Filter with the MRPT C++ libraries.
- The Kalman Filter Explained A very simple tutorial.
- The Kalman Filter in Reproducing Kernel Hilbert Spaces A comprehensive introduction.
- Matlab code to estimate Cox–Ingersoll–Ross interest rate model with Kalman Filter: Corresponds to the paper "estimating and testing exponential-affine term structure models by kalman filter" published by Review of Quantitative Finance and Accounting in 1999.
- Extended Kalman Filters explained in the context of Simulation, Estimation, Control, and Optimization
- Online demo of the Kalman Filter. Demonstration of Kalman Filter (and other data assimilation methods) using twin experiments.
- Handling noisy environments: the k-NN delta s, on-line adaptive filter. in Robust high performance reinforcement learning through weighted k-nearest neighbors, Neurocomputing, 74(8), March 2011, pp. 1251–1259.