Identification Method of Power Spectral Signal Based on Fourier Series Fitting and Density Clustering

Author(s):  
Xiaodong Bai ◽  
Wendeng Zhu ◽  
Gengxin Zhang ◽  
Tao Hong ◽  
Laiding Zhao ◽  
...  
Author(s):  
M. Unser ◽  
B.L. Trus ◽  
A.C. Steven

Since the resolution-limiting factor in electron microscopy of biological macromolecules is not instrumental, but is rather the preservation of structure, operational definitions of resolution have to be based on the mutual consistency of a set of like images. The traditional measure of resolution for crystalline specimens in terms of the extent of periodic reflections in their diffraction patterns is such a criterion. With the advent of correlation averaging techniques for lattice rectification and the analysis of non-crystalline specimens, a more general - and desirably, closely compatible - resolution criterion is needed. Two measures of resolution for correlation-averaged images have been described, namely the differential phase residual (DPR) and the Fourier ring correlation (FRC). However, the values that they give for resolution often differ substantially. Furthermore, neither method relates in a straightforward way to the long-standing resolution criterion for crystalline specimens.


1997 ◽  
Vol 36 (04/05) ◽  
pp. 41-46
Author(s):  
A. Kjaer ◽  
W. Jensen ◽  
T. Dyrby ◽  
L. Andreasen ◽  
J. Andersen ◽  
...  

Abstract.A new method for sleep-stage classification using a causal probabilistic network as automatic classifier has been implemented and validated. The system uses features from the primary sleep signals from the brain (EEG) and the eyes (AOG) as input. From the EEG, features are derived containing spectral information which is used to classify power in the classical spectral bands, sleep spindles and K-complexes. From AOG, information on rapid eye movements is derived. Features are extracted every 2 seconds. The CPN-based sleep classifier was implemented using the HUGIN system, an application tool to handle causal probabilistic networks. The results obtained using different training approaches show agreements ranging from 68.7 to 70.7% between the system and the two experts when a pooled agreement is computed over the six subjects. As a comparison, the interrater agreement between the two experts was found to be 71.4%, measured also over the six subjects.


ICCTP 2011 ◽  
2011 ◽  
Author(s):  
Xing-jian Zhang ◽  
Xiao-hua Zhao ◽  
Jian Rong ◽  
Shi-li Xu

2012 ◽  
Vol 132 (2) ◽  
pp. 231-237
Author(s):  
Yuuki Imanara ◽  
Kota Itakura ◽  
Masaki Samejima ◽  
Masanori Akiyoshi

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