The DOI matches its Crossref record; 11 of the 11 references it cites were found in a registry or an index.
Partitioning: A unifying framework for adaptive systems, I: Estimation
Abstract
In this paper, partitioning and the associated generalized partitioned estimation algorithms are shown to constitute a unifying and powerful framework for optimal adaptive estimation in linear as well as nonlinear problems. Using the partitioning framework, the adaptive estimation problem is treated from a global viewpoint that readily yields and unifies seemingly unrelated results and, most importantly, yields fundamentally new families of nonlinear and linear estimation algorithms in a decoupled parallel-realization form. The generalized partitioned estimation algorithms are shown to have several important properties from both a theoretical and a realization or computational standpoint.
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Citations
Cites
Stochastic Processes and Filtering Theory
(1970) · Mathematics in Science and Engineering · doi:10.1016/s0076-5392(09)x6022-4 · Cited by 7,302
Nonlinear Bayesian estimation using Gaussian sum approximations
Alspach, D., & Sorenson, H. (1972) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1972.1100034 · Cited by 1,239
Optimal adaptive estimation of sampled stochastic processes
Magill, D. (1965) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1965.1098191 · Cited by 786
Kailath, T. (1968) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1968.1099025 · Cited by 742
Some Applications of Stochastic Differential Equations to Optimal Nonlinear Filtering
Wonham, W. M. (1964) · Journal of the Society for Industrial and Applied Mathematics Series A Control · doi:10.1137/0302028 · Cited by 423
Advances in Pattern Recognition
Casey, R. G., & Nagy, G. (1971) · Scientific American · doi:10.1038/scientificamerican0471-56 · Cited by 292
Leondes, C. T., Peller, J. B., & Stear, E. B. (1970) · IEEE Transactions on Systems Science and Cybernetics · doi:10.1109/tssc.1970.300330 · Cited by 88
Joint detection, estimation and system identification
LAINIOTIS, D. G. (1971) · Information and Control · doi:10.1016/s0019-9958(71)80008-6 · Cited by 55
Self-citationNew smoothing algorithms based on reversed-time lumped models
Sidhu, G. K., & Desai, U. B. (1976) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1976.1101289 · Cited by 51
General backwards Markov models
LAINIOTIS, D. G. (1976) · IEEE Transactions on Automatic Control · doi:10.1109/tac.1976.1101281 · Cited by 21
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Survey of maneuvering target tracking. part v: multiple-model methods
Li, X. R., & Jilkov, V. P. (2005) · IEEE Transactions on Aerospace and Electronic Systems · doi:10.1109/taes.2005.1561886 · Cited by 1,157
A Review on Kalman Filter Models
Khodarahmi, M., & Maihami, V. (2023) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-022-09815-7 · Cited by 561
Modeling, Clustering, and Segmenting Video with Mixtures of Dynamic Textures
Chan, A. B., & Vasconcelos, N. (2008) · IEEE Transactions on Pattern Analysis and Machine Intelligence · doi:10.1109/tpami.2007.70738 · Cited by 459
New algorithms for aircraft intent inference and trajectory prediction
Yepes, J. L., Hwang, I., & Rotea, M. (2007) · Journal of Guidance, Control, and Dynamics · doi:10.2514/1.26750 · Cited by 162
Metadata
- Authors
- Lainiotis, D. G.
- Venue
- Proceedings of the IEEE
- Published
- 1976
- Volume
- 64
- Issue
- 8
- Pages
- 1126-1143
- ISSN
- 0018-9219 (ISSN-L)
- OpenAlex
- W1978294824
- Cited by
- 338
- References
- 11
- FWCI
- 18.32
- Type
- journal article
- Language
- en
- Open access
- closed
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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