Global ETD Search

1. 1

   The Synchronized Filtering Dataflow

   Li, Peng2014

   … of its output channels. This behavior, known as filtering, is data-dependent and unpredictable. When filtered data streams are synchronized, applications can deadlock due to empty and full channel buffers.</p><p>To avoid deadlocks and ensure bounded-memory execution, we turn to model-based …

   wustl Repository record for The Synchronized Filtering Dataflow (opens in a new tab)

2. 2

   Duality for nonlinear filtering

   Kim, Jin WonUniversity of Illinois at Urbana-Champaign2022

   Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-11-15 without embargo terms

   uiuc Repository record for Duality for nonlinear filtering (opens in a new tab)

3. 3

   Parametric non-linear filtering

   Lamb, Richard HubbertMassachusetts Institute of Technology1987

   Thesis (Sc. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1987.

   mit Repository record for Parametric non-linear filtering (opens in a new tab)

4. 4

   Filtering for bilinear systems

   Vallot, Lawrence CharlesMassachusetts Institute of Technology1981

   Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1981.

   mit Repository record for Filtering for bilinear systems (opens in a new tab)

5. 5

   Partial Update Adaptive Filtering

   Xie, BeiVirginia Tech2011

   … different PU methods or among different adaptive filtering algorithms. Computational complexity is calculated for each PU method and each adaptive filter algorithm. The deficient-length RLS and EDS are also analyzed and compared to the performance of the PU adaptive filter. In this dissertation, …

   vt Repository record for Partial Update Adaptive Filtering (opens in a new tab)

6. 6

   Spatial Filtering for Small Objects

   Chesire, Daniel Patrick1975

   No abstract prepared.

   tdl Repository record for Spatial Filtering for Small Objects (opens in a new tab)

7. 7

   Information filtering by multiple examples

   Zhu, Mingzhu

   … research proposes a framework named Information Filtering by Multiple Examples (IFME) to explore how to improve SBME by: (1) solving the topic diversity issue by adopting probabilistic topic models to predict user's information need from the query examples; (2) tackling the class imbalance …

   njit Repository record for Information filtering by multiple examples (opens in a new tab)

8. 8

   Realising context-oriented information filtering.

   Webster, David EdwardUniversity of Hull2010

   … us.The development of a model to aid information filtering in a context-aware way is developed as an objective for this thesis. A key concern in the conceptualisation of a single concept is understanding the context under which that concept exists (or can exist). An example of a concept is a …

   hull Repository record for Realising context-oriented information filtering. (opens in a new tab)

9. 9

   Robust credibility and Kalman filtering

   Tam, Mike1998

   … models are presented via robust Kalman filtering. Credibility theory has been shown to be a special case of the Kalman filter (De Jong and Zehnwirth, 1983), thus existing research on the robustification of the Kalman filter, for example, Cipra and Romera (1991), can be applied to …

   concordia Repository record for Robust credibility and Kalman filtering (opens in a new tab)

10. 10

    Martingales in Filtering and Geometry

    Bauer, Robert OttoUniversity of Illinois at Urbana-Champaign2015

    We give three applications of martingale theory. First, we study a problem in real-time target tracking. Realistic assumptions, namely limited processing power, turn the variance into a stochastic process. We transform and compensate the variance process so as to obtain a martingale. We find …

    uiuc Repository record for Martingales in Filtering and Geometry (opens in a new tab)

11. 11

    New Adaptive Iir Filtering Algorithms

    Fan, HongUniversity of Illinois at Urbana-Champaign2014

    A family of adaptive IIR filtering algorithms is proposed based on the Steiglitz-McBride identification scheme. The algorithms are shown to be close approximations of one another for slow adaptation. Because of the non-vanishing gain, they are suitable for filtering applications and are simple to …

    uiuc Repository record for New Adaptive Iir Filtering Algorithms (opens in a new tab)

12. 12

    Comparison of nonlinear filtering techniques

    Ghiotto, ShaneUniversity of Illinois at Urbana-Champaign2014

    … structure inspired by traditional nonlinear filtering combined with optimal control formalisms. The resulting algorithm is referred to as feedback particle filter. The purpose of this thesis is to provide a comparative study of the feedback particle filter (FPF). Two types of comparisons are …

    uiuc Repository record for Comparison of nonlinear filtering techniques (opens in a new tab)

13. 13

    Robust adaptive control and filtering

    Naik, Sanjeev ManubhaiUniversity of Illinois at Urbana-Champaign2011

    … of various adaptive systems for control, filtering, and identification. These include the uniform boundedness or mean-square boundedness of all closed-loop signals (robust boundedness, robust ultimate boundedness), the closed-loop system tracking error performance in the presence (robust …

    uiuc Repository record for Robust adaptive control and filtering (opens in a new tab)

14. 14

    Meta-learning for adaptive filtering

    Casebeer, JonahUniversity of Illinois at Urbana-Champaign2023

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2024-03-01 without embargo terms

    uiuc Repository record for Meta-learning for adaptive filtering (opens in a new tab)

15. 15

    Collaborative filtering with low regret

    Voloch, Luis FMassachusetts Institute of Technology2015

    Collaborative filtering (CF) is a widely used technique in recommendation systems where recommendations are provided in a content-agnostic manner, and there are two main paradigms in neighborhood-based CF: the user-user paradigm and the item-item paradigm. To recommend to a user in the user-user …

    mit Repository record for Collaborative filtering with low regret (opens in a new tab)

16. 16

    Wavenumber filtering by mechanical structures

    Martin, Nathan ClayMassachusetts Institute of Technology1976

    Thesis. 1976. Sc.D.--Massachusetts Institute of Technology. Dept. of Mechanical Engineering.

    mit Repository record for Wavenumber filtering by mechanical structures (opens in a new tab)

17. 17

    Topics in nonlinear filtering theory

    Ocone, DanielMassachusetts Institute of Technology1980

    Thesis (Ph.D.)--Massachusetts Institute of Technology, Dept. of Mathematics, 1980.

    mit Repository record for Topics in nonlinear filtering theory (opens in a new tab)

18. 18

    Feature guided automated collaborative filtering

    Lashkari, Yezdezard ZerxesMassachusetts Institute of Technology1995

    Thesis (M.S.)--Massachusetts Institute of Technology, Program in Media Arts & Sciences, 1995.

    mit Repository record for Feature guided automated collaborative filtering (opens in a new tab)

19. 19

    Image sequence restoration by median filtering

    Jackson, Shawn R.

    rit Repository record for Image sequence restoration by median filtering (opens in a new tab)

20. 20

    Adaptive algorithms for two dimensional filtering.

    Wilstrup, Steven L.Monterey, California. Naval Postgraduate School1988

    nps Repository record for Adaptive algorithms for two dimensional filtering. (opens in a new tab)

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