S. Haykin, P. Lee, E. Derbez, "Optimum nonlinear filtering", IEEE Transactions on Signal Processing, Vol. 45, no. 11, pp.2774-2786, 1997. Home/Search Document Details and Download
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Rational-Based Adaptive Fuzzy Filters - Khriji, Gabbouj (2004) (Correct)
....Vector magnitude filters, Vector directional filters, Color image processing. This work was completed with the support of Sultane Qaboos University, Oman, and the Institute of Signal Processing, TUT, Finland. #2003 2004 Yang s Scientific Research Institute, LLC. All rights reserved. 113 [8, 11]. In order to cope with all these problems; several techniques have been introduced and developed over the years, quite often with greet success. Among them are linear processing techniques; whose mathematical simplicity and the existence of a unifying theory make their design and implementation ....
S. Haykin, P. Lee, E. Derbez, "Optimum nonlinear filtering", IEEE Transactions on Signal Processing, Vol. 45, no. 11, pp.2774-2786, 1997.
On Estimators For Nonlinear Systems In Lp Spaces - Alessandri, Sanguineti (2000) (Correct)
....inputs or as stochastic random variables within a probabilistic framework. The former approach enables one to design recursive estimators, according to a least squares estimation criterion. The probabilistic approach has brought to different kinds of solutions# the reader is referred to [9] for an introductiontothis subject. In this paper the estimation problem is addressed for continuous time nonlinear dynamic systems in a general framework of L p signals# in such a context, the connection between the observation and the filtering problems is investigated. Basic notations and ....
S. Haykin, P. Yee, and E. Derbez, "Optimum nonlinear filtering", IEEE Trans. on Signal Processing,vol. 45, no. 11, pp. 2774--2786, 1997.
Design of Sliding-Mode Observers and Filters for Nonlinear.. - Alessandri (Correct)
....a filter is frequently used in practical applications and may be obtained by applying the Kalman filter to the state and channel equations linearized around the last estimated state vector. As far as other approaches are concerned, the most recent advances in nonlinear filtering are reported in [3]. If there is no noise affecting the system and channel equations, the problem of state reconstruction can be faced using various techniques [4, 5] One solution consists in applying a canonical state space transformation so as to concentrate nonlinearities to a function dependent only on known ....
S. Haykin, P.Yee, and E. Derbez, "Optimum nonlinear filtering", IEEE Trans. on Signal Processing,vol. 45, no. 11, pp. 2774--2786, November 1997.
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