JOSÉ DOMINGO
JIMÉNEZ LÓPEZ
TITULAR DE UNIVERSIDAD
Kagoshima University
Kagoshima, JapónPublications in collaboration with researchers from Kagoshima University (15)
2010
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Signal estimation with multiple delayed sensors using covariance information
Digital Signal Processing: A Review Journal, Vol. 20, Núm. 2, pp. 528-540
2009
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Recursive estimation of discrete-time signals from nonlinear randomly delayed observations
Computers and Mathematics with Applications, Vol. 58, Núm. 6, pp. 1160-1168
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Signal estimation with nonlinear uncertain observations using covariance information
Journal of Statistical Computation and Simulation, Vol. 79, Núm. 1, pp. 55-66
2008
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Nonlinear Estimation of Discrete-Time Signals under Random Observation Delay
AIP Conference Proceedings
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Polynomial fixed-point smoothing of uncertainly observed signals based on covariances
International Journal of Systems Science, Vol. 39, Núm. 2, pp. 207-216
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Recursive estimation algorithm based on covariances for uncertainly observed signals correlated with noise
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences, Vol. E91-A, Núm. 7, pp. 1706-1712
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Recursive fixed-point smoothing algorithm from covariances based on uncertain observations with correlation in the uncertainty
Applied Mathematics and Computation, Vol. 203, Núm. 1, pp. 243-251
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Signal estimation based on covariance information from observations featuring correlated uncertainty and coming from multiple sensors
Signal Processing, Vol. 88, Núm. 12, pp. 2998-3006
2007
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Signal polynomial smoothing from correlated interrupted observations based on covariances
Mathematical Methods in the Applied Sciences
2006
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Least-squares νth-order polynomial estimation of signals from observations affected by non-independent uncertainty
Applied Mathematics and Computation, Vol. 176, Núm. 2, pp. 642-653
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Recursive estimation of the false alarm probablility using approximations of mixtures
Proceedings of the IASTED International Conference on Modelling, Identification, and Control, MIC
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Signal estimation algorithm from uncertain observations with signal and coloured noise correlated at any sampling time
Proceedings of the IASTED International Conference on Modelling, Identification, and Control, MIC
2005
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An innovation approach to the smoothing problem from uncertain observations with correlated signal and noise
Mathematical Methods in the Applied Sciences, Vol. 28, Núm. 13, pp. 1569-1584
2004
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Chandrasekhar-type filter for a wide-sense stationary signal from uncertain observations using covariance information
Applied Mathematics and Computation, Vol. 151, Núm. 2, pp. 315-325
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Chandrasekhar-type recursive Wiener filter using covariance information in linear discrete-time wide-sense stationary stochastic systems
IFAC Proceedings Volumes (IFAC-PapersOnline)