Gradient Pattern Analysis
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High Quality Content by WIKIPEDIA articles! Gradient pattern analysis (GPA) is a geometric computing method for characterizing symmetry breaking of an ensemble of asymmetric vectors regularly distributed in a square lattice. Usually, the lattice of vectors represent the first-order gradient of a scalar field, here an M x M square amplitude matrix (mathematics). An important property of the gradient representation is the following: A given M x M matrix where all amplitudes are different results in an M x M gradient lattice containing NV = M2 asymmetric vectors. As each vector can be characteriz...
High Quality Content by WIKIPEDIA articles! Gradient pattern analysis (GPA) is a geometric computing method for characterizing symmetry breaking of an ensemble of asymmetric vectors regularly distributed in a square lattice. Usually, the lattice of vectors represent the first-order gradient of a scalar field, here an M x M square amplitude matrix (mathematics). An important property of the gradient representation is the following: A given M x M matrix where all amplitudes are different results in an M x M gradient lattice containing NV = M2 asymmetric vectors. As each vector can be characterized by its norm and phase, variations in the M2 amplitudes can modify the respective M2 gradient pattern.
