Seizure prediction using cross-correlation and classification

Author(s):  
Zisheng Zhang ◽  
Thomas R. Henry ◽  
Keshab K. Parhi
Author(s):  
Claudia C. Botero Suarez ◽  
Erich Talamoni Fonoff ◽  
Mario Alonso Munoz G ◽  
Antonio Carlos Godoi ◽  
Gerson Ballester ◽  
...  

Author(s):  
Douglas L. Dorset ◽  
Barbara Moss

A number of computing systems devoted to the averaging of electron images of two-dimensional macromolecular crystalline arrays have facilitated the visualization of negatively-stained biological structures. Either by simulation of optical filtering techniques or, in more refined treatments, by cross-correlation averaging, an idealized representation of the repeating asymmetric structure unit is constructed, eliminating image distortions due to radiation damage, stain irregularities and, in the latter approach, imperfections and distortions in the unit cell repeat. In these analyses it is generally assumed that the electron scattering from the thin negativelystained object is well-approximated by a phase object model. Even when absorption effects are considered (i.e. “amplitude contrast“), the expansion of the transmission function, q(x,y)=exp (iσɸ (x,y)), does not exceed the first (kinematical) term. Furthermore, in reconstruction of electron images, kinematical phases are applied to diffraction amplitudes and obey the constraints of the plane group symmetry.


Author(s):  
D. E. Luzzi ◽  
L. D. Marks ◽  
M. I. Buckett

As the HREM becomes increasingly used for the study of dynamic localized phenomena, the development of techniques to recover the desired information from a real image is important. Often, the important features are not strongly scattering in comparison to the matrix material in addition to being masked by statistical and amorphous noise. The desired information will usually involve the accurate knowledge of the position and intensity of the contrast. In order to decipher the desired information from a complex image, cross-correlation (xcf) techniques can be utilized. Unlike other image processing methods which rely on data massaging (e.g. high/low pass filtering or Fourier filtering), the cross-correlation method is a rigorous data reduction technique with no a priori assumptions.We have examined basic cross-correlation procedures using images of discrete gaussian peaks and have developed an iterative procedure to greatly enhance the capabilities of these techniques when the contrast from the peaks overlap.


1989 ◽  
Vol 50 (C8) ◽  
pp. C8-97-C8-102 ◽  
Author(s):  
J. BEBEN ◽  
CH. KLEINT ◽  
R. MECLEWSKI

2011 ◽  
Vol 29 (supplement) ◽  
pp. 283-304 ◽  
Author(s):  
Timothy R. Brick ◽  
Steven M. Boker

Among the qualities that distinguish dance from other types of human behavior and interaction are the creation and breaking of synchrony and symmetry. The combination of symmetry and synchrony can provide complex interactions. For example, two dancers might make very different movements, slowing each time the other sped up: a mirror symmetry of velocity. Examining patterns of synchrony and symmetry can provide insight into both the artistic nature of the dance, and the nature of the perceptions and responses of the dancers. However, such complex symmetries are often difficult to quantify. This paper presents three methods – Generalized Local Linear Approximation, Time-lagged Autocorrelation, and Windowed Cross-correlation – for the exploration of symmetry and synchrony in motion-capture data as is it applied to dance and illustrate these with examples from a study of free-form dance. Combined, these techniques provide powerful tools for the examination of the structure of symmetry and synchrony in dance.


2013 ◽  
Vol 58 (2) ◽  
pp. 122-125 ◽  
Author(s):  
O.V. Gnatovskyy ◽  
◽  
A.M. Negriyko ◽  
V.O. Gnatovskyy ◽  
A.V. Sidorenko ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document