This study is the following steps: first extract facial feature vector generate training and testing samples reuse create LVQ neural network model, which is trained using training samples to adjust the weights using the test sample towards the establishment of a human face recognition model validated requires a higher recognition rate. This topic requires the use of LVQ neural network algorithm Matlab simulation, the human face towards effective judgment and identification.

feature_extraction.m
lvqnew.m
lvqnew.asv
strm.m
untitled.fig
untitled.m
untitled.asv
图片 002_副本.bmp
chapter22_bp.m
chapter22_lvq.m

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