Results 201 to 210 of about 1,686,514 (289)

A deep-learning model for one-shot transcranial ultrasound simulation and phase aberration correction. [PDF]

Med Phys
Naftchi-Ardebili K, Singh K, Popelka GR, Pauly KB.   +3 more
europepmc   +1 more source

Automated characterisation of cerebral microbleeds using their size and spatial distribution on brain MRI. [PDF]

Eur Radiol Exp
Sundaresan V, Zamboni G, Dineen RA, Auer DP, Sotiropoulos SN, Sprigg N, Jenkinson M, Griffanti L.   +7 more
europepmc   +1 more source

A detection method for small casting defects based on bidirectional feature extraction. [PDF]

Sci Rep
Zhang S, Li H, Ren P, Peng T, Meng X.
europepmc   +1 more source

Identifying phenotype-genotype-function coupling in 3D organoid imaging using Shape, Appearance and Motion Phenotype Observation Tool (SPOT)

Zhou FY, Jacobs B, Norton-Steele A, Han X, Zhou L, Carroll TM, Ruiz Puig C, Chadwick J, Qin X, Lisle R, Marsh L, Byrne HM, Harrington HA, Lu X.   +13 more
europepmc   +1 more source

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Bounded-error estimation using dead zone and bounding ellipsoid

International Journal of Adaptive Control and Signal Processing, 1994
AbstractThe use of a dead zone and a bounding ellipsoid for parameter estimation when measurement errors are bounded is discussed. the size of the dead zone is set to be exactly equal to the assumed noise bound. The algorithm retains the properties of computing parameter point estimates and allows a bounding ellipsoid to be computed at each iterative ...
R. Evans, C. Zhang, Y. Soh
semanticscholar   +2 more sources

Multiweight optimization in optimal bounding ellipsoid algorithms

IEEE Transactions on Signal Processing, 2006
Optimal Bounding Ellipsoid (OBE) algorithms offer an attractive alternative to traditional least-squares methods for identification and filtering problems involving affine-in-parameters signal and system models. The benefits-including low computational efficiency, superior tracking ability, and selective updating that permits processor multi-tasking ...
D. Joachim, J. Deller
semanticscholar   +2 more sources

Recurrent Neural Networks Training With Stable Bounding Ellipsoid Algorithm

IEEE Transactions on Neural Networks, 2009
Bounding ellipsoid (BE) algorithms offer an attractive alternative to traditional training algorithms for neural networks, for example, backpropagation and least squares methods. The benefits include high computational efficiency and fast convergence speed.
Wen Yu, J. J. Rubio
semanticscholar   +3 more sources

Stochastic Convergence of Optimal Bounding Ellipsoid Algorithms

Journal of Circuits, Systems and Computers, 1997
Given appropriate persistency of excitation, the ellipsoidal seta associated with optimal bounding ellipsoid (OBE) algorithms with an interpretable optimization (volume) criterion, converge to a point under the condition that the model disturbance process visit the error bounds infinitely often.
M. Nayeri, J. Deller, Ming-Shou Liu
semanticscholar   +2 more sources

Automatic bound estimation: a practical development in optimal bounding ellipsoid processing

IEEE Signal Processing Letters, 1997
Practical application of optimal bounding ellipsoid identification is made possible by the optimal bounding ellipsoid algorithm with automatic bound estimation (OBE-ABE), which automatically estimates model error bounds. Lack of tenable bounds in many real problems has rendered these interesting new methods impractical.
Tsung-Ming Lin, M. Nayeri, J. Deller
semanticscholar   +2 more sources