Nanocrystalline collagen-based bone materials in skeletal optimization in patients

Abstract

In order to improve the feature extraction ability of nanofibers, a feature detection method based on non-linear mapping pattern recognition is proposed. The cluster–cluster hybrid molecular reconstruction method is used to deal with the spatial spectrum beamforming of nanofiber features, and the recursive graph analysis method is used to decompose the association rule features of nanofibers to realize the non-linear mapping pattern recognition of nanofiber features. Combined with the related attribute-clustering method, the characteristics of nanofibers are classified and identified to achieve the optimization of nanofiber feature detection. The simulation results show that the method has high accuracy, good performance of pattern recognition of non-linear mapping and good ability of accurate recognition of the crystal structure characteristics of nanofibers.