Application of fuzzy neural networks for defining crystal lattice types in nanoscale images
О. П. Солдатова, I. Lyozin, I.V. Lyozina, Alexander V. Kupriyanov, Dmitriy V. Kirsh · Computer Optics · 2015
The article proposes the application of neural fuzzy networks for defining the overlapping classes of crystal lattices. We discuss the following neural fuzzy networks: Takagi-Sugeno-Kung network and a modification of Wang-Mendel neural fuzzy network proposed by the authors. A three-step scheme of neural network training is proposed. The results prove the efficiency of the proposed approach for the determination of crystal lattice types.