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Gradient Pattern Analysis: Symmetry, Gradient, Matrix (mathematics) -

Anglų
2026-03-17
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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 represen ... Visas aprašymas

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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 characterized by its norm and phase, variations in the M2 amplitudes can modify the respective M2 gradient pattern.

Daugiau informacijos

Leidėjas OmniScriptum
Išleidimo metai 2026
Viršelio tipas Minkšti viršeliai
EAN 9786131167454
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183,70 € 282,62 €