Multiple source location estimation using the EM Algorithm
MetadataShow full item record
We present a computationally efficient scheme for multiple source location estimation based on the EM Algorithm. The proposed scheme is optimal in the sense that it converges iteratively to the exact Maximum Likelihood estimate for all the unknown parameters simultaneously. The method can be applied to a wide range of problems arising in signal and array processing.
Showing items related by title, author, creator and subject.
Loose, Brice; Jenkins, William J.; Moriarty, Roisin; Brown, Peter; Jullion, Loic; Naveira Garabato, Alberto C.; Valdes, Sinhue Torres; Hoppema, Mario; Ballentine, Chris; Meredith, Michael P. (John Wiley & Sons, 2016-08-18)The distribution of noble gases and helium isotopes in the dense shelf waters of Antarctica reflects the boundary conditions near the ocean surface: air-sea exchange, sea ice formation, and subsurface ice melt. We use a ...
Estimation of ocean subsurface thermal structure from surface parameters : a neural network approach Ali, M. M.; Swain, D.; Weller, Robert A. (American Geophysical Union, 2004-10-22)Satellite remote sensing provides diverse and useful ocean surface observations. It is of interest to determine if such surface observations can be used to infer information about the vertical structure of the ocean's ...
Estimating hydrodynamic roughness in a wave-dominated environment with a high-resolution acoustic Doppler profiler Lacy, Jessica R.; Sherwood, Christopher R.; Wilson, Douglas J.; Chisholm, Thomas A.; Gelfenbaum, Guy R. (American Geophysical Union, 2005-06-30)Hydrodynamic roughness is a critical parameter for characterizing bottom drag in boundary layers, and it varies both spatially and temporally due to variation in grain size, bedforms, and saltating sediment. In this paper ...