多尺度系统理论研究概况

赵巍; 潘泉; 戴冠中; 张洪才

多尺度系统理论研究概况

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出版历程
- 收稿日期: 2000-05-10
- 修回日期: 2000-10-12
- 刊出日期: 2001-12-19

DEVELOPMENT OF MULTISCALE SYSTEM THEORY

摘要

摘要: 在许多应用领域中,通常要对出现在不同尺度的现象进行分析和辨识,最近引入的多尺度框架使这一分析成为可能。该文简单介绍了多尺度系统理论的发展概况以及多尺度框架在估计和数据融合中的应用,分析了多尺度模型、平滑误差模型以及两类多尺度实现模型,并指出了目前急需解决的问题。
- 多尺度建模; 多尺度平滑算法; 内部实现模型; 外部实现模型
Abstract: In many problems, it is of interest to analyze and recognize the phenomena occurring at different scales. The recently introduced multiscale framework offers the possibility of such an analysis. In this paper; the development of the multiscale system theory is introduced briefly, and its application in modeling and estimation is presented. The multiscale models, smoothing error models and two kinds of multiscale realizations are described in particular. Some possible research directions are pointed out.

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H. Krim, W. Willinger, A. Juditski, D. Tse. Introduction to the special issue on multiscale statistical signal analysis and its application, IEEE Trans. on Information Theory, 1999, 45(3),825-827.[2]M. Basseville, A. Benveniste, K. Chou, S. Golden, R. Nikoukhah, A. Willsky, Modeling and estimation of multiresolution stochastic process, IEEE Trans. on Information Theory, 1992,38(2), 766-784.[3]K. Chou, A. Willsky, A. Benveniste, Multiscale recursive estimation, data fusion and regularization, IEEE Trans. on Automatic Control, 1994, 39(3), 464-478.[4]A. Benveniste, R. Nikoukhah, A. Willsky, Multiscale system theory, in Proc. 29th IEEE Conference on Decision and Control, Honolulu, Hawaii, Dec. 1990, 2484-2487.[5]M. Basseville, A. Benveniste, A. Willsky, Multiscale autoregressive processes, Part I, Schur-Levinson parametrizations, IEEE Trans. on Signal Processing, 1992, 40(8), 1915-1934.[6]M. Basseville, A. Benveniste, A. Willsky, Multiscale autoregressive processes, Part II, Lattice structure for whitening and modeling, IEEE Trans. on Signal Processing, 1992, 40(8), 1935-1953.[7]K. Chou, A. Willsky. Kalman filtering and Riccati equations for multiscale processes, in Proc.29th IEEE Conference on Decision and Control, Honolulu, Hawaii, Dec. 1990, 841-846.[8]K. Chou, S. A. Golden, A. Willsky, Multiresolution stochastic models, data fusion and wavelet transform, Signal Processing, 1993, 34(3), 257-282.[9]K. Chou, A. Willsky, R. Nikoukhah, Multiscale systems, Kalman filters and Riccati equations,IEEE Trans. on Automatic Control, 1994, 39(3), 479-492.[10]M. Bello, A. Willsky, B. Levy, D. Castanon, Smoothing error dynamics and their use in the solution of smoothing and mapping problems, IEEE Trans. on Information Theory, 1986, 32(4),483-495.[11]M. Bello, A. Willsky, B. Levy, Construction and application of discrete-time smoothing error models, Int. J. Contr., 1989, 50(1), 203-223.[12]M. R. Luettgen, A. Willsky, Multiscale smoothing error models, IEEE Trans. on Automat.Contr., 1995, 40(1), 173-175.[13]M.R. Luettgen, Image processing with multiscale stochastic models. [PhD thesis], Massachusetts Institute of Technology, Cambridge, MA, 1993. ［14］M. R. Luettgen, A. Willsky, Likelihood calculation for a class of multiscale stochastic models, with application to texture discrimination, IEEE Trans. on Image Processing, 1995, 4(2), 194-207.[14]P.W. Feiguth, A. Willsky, Fractal estimation using model on multiscale trees, IEEE Trans. on Signal Processing, 1996, 44(5), 1297-1300.[15]P. Fieguth, W. Karl, A. Willsky, C. Wunsch, Multiresolution optimal interpolation and statistical analysis of TOPEX/POSEIDON satellite altimetry, IEEE Trans. on Geoscience and Remote Sensing, 1995, 33(2), 280-292.[16]P. Fieguth, D. Menemenlis, T. Ho, A. Willsky, C. Wunsch, Mapping Mediterranean altimeter data with a multiresolution optimal interpolation algorithm, J. of Atmospheric and Oceanic Technology, 1998, 15(4), 535-546.[17]M.R. Luettgen, W. C. Karl, A. Willsky, Multiscale representation of Markov random fields, IEEE Trans. on Signal Processing, 1993, 41(12), 3377-3395.[18]D. Menemenlis, P. Fieguth, C. Wunsch, A. Willsky, Adaptation of a fast optimal interpolation algorithm to the mapping of oceanographic data, J. of Geophysical Research, 1997, 102(C5),10573-10584.[19]W. Irving, P. Fieguth, A. Willsky, An overlapping tree approach tb multiscale stochastic modeling and estimation, IEEE Trans. on Image Processing, 1997, 6(11), 1517-1729.[20]T. T. Ho. Multiscale modeling and estimation of large-scale dynamic systems. [PhD thesis],Massachusetts Institute of Technology, Cambridge, MA, 1998. ［22］M. Daniel, A. Willsky, A multiresolution methodology for signal-level fusion and data assimilation with applications to remote sensing, Proc. IEEE, 1997, 85(1), 164-183.[21]W. Irving, Theory for multiscale stochastic realization and identification. [PhD thesis], Massachusetts Institute of Technology, Cambridge, MA, 1995. ［24］H. Akaike, Markovian representation of stochastic processes by canonical variables, SIAM J. of Control, 1975, 13(1), 162-173.[22]M. Luettgen, W. Karl, A. Willsky, Efficient multiscale regulation with application to the computation of optical flow, IEEE Trans. on Image Processing, 1994, 3(1), 41-64.[23]P. Fieguth, W. Karl, A. Willsky, Efficient multiresolution counterparts to variational methods in surface reconstruction, Coy puter Vision and Image Understanding, 1998, 70(2), 157-176.[24]M. Schneider.[J].Multiscale methods for the segmentation of images, [Masters thesis], Massachusetts Institute of Technologv, Cambridge, MA.1996,:-[25]赵巍,多尺度系统建模与估计方法研究,博士论文,西北工业大学,2001年.

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