Gradient pattern analysis: Difference between revisions

Revision as of 05:21, 26 March 2009

Revision as of 13:48, 31 March 2009

Line 6:

By connecting all vectors using a [[Delaunay triangulation]] criterion it is possible to characterize gradient assymetries computing the so-called ''gradient asymmetry coefficient'', that has been defined as:

<math>G_A=\frac{|N_C-N_V|}{N_V}</math>,

where <math>N_{V} > 0</math> is the total number of asymmetric vectors and, <math>N_{C}</math> is the number of Delaunay connections among them. and the property <math>N_{C} > N_{V}</math>

is valid for any gradient square lattice.

As the asymmetry coefficient is very sensitive to small changes in the phase and modulus of each gradient vector, it can distinguish complex variability patterns even when they are very similar but consist of a very fine structural difference. Not that, unlike most of the statistical tools, the GPA does not rely on the statistical properties of the data but