Titlebook: Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series; A. Ramachandra Rao,En-Ching Hsu Book 2008 Springer Science

有帮助

Adrenal-Glands

唤醒

A. Ramachandra Rao,En-Ching Hsu, 10 with WML and 10 controls as part of the process of applying deep machine learning and preparing a training set for the automated detection of WML. Participants under went 1.5 T 3D-T1v, MPRAGE and 3D FLAIR MRI. Images were aligned with MNI space to normalize their intensity. Manual segmentation

薄膜

Immunization

A. Ramachandra Rao,En-Ching Hsuwo affine sub-spaces, can be used to modify related learning methods, prevent undesirable scenarios, and gain insights about the geometry of the data set. We will show that the decision borders, that are basically quadratic surfaces, can be affine spaces, Hyper-Cones, or hyperbolic paraboloids embed

改革运动

A. Ramachandra Rao,En-Ching Hsu as superposition or entanglement. The laws of quantum mechanics can reduce the required resources for some tasks by many orders of magnitude if the image data is encoded in the quantum state of a suitable physical system. The aim of this work is to develop and study quantum models of image transfor

沉默

A. Ramachandra Rao,En-Ching Hsumization turns out to ensure robustness with respect to the presence of noise or occlusion in the images. Moreover, combining the optimized centroids yields more robust results than a method using simple centroids with a highly robust correlation coefficient (with a high breakdown point).

Pastry

mization turns out to ensure robustness with respect to the presence of noise or occlusion in the images. Moreover, combining the optimized centroids yields more robust results than a method using simple centroids with a highly robust correlation coefficient (with a high breakdown point).

喃喃诉苦

0921-092X eamflow, temperature, wind speed time series and lake temperature data are investigated in this study. The aim of the work is to investigate periodicity, long t978-90-481-7645-8978-1-4020-6454-8Series ISSN 0921-092X Series E-ISSN 1872-4663

calamity

Hilbert-Huang Transform Analysis of Hydrological and Environmental Time Series