| 摘要 |
PROBLEM TO BE SOLVED: To provide a pattern classification device for making vector data high-dimensional based on multiple linear mapping and extracting and classifying pattern features of the vector data, a pattern classification method and a pattern classification program.SOLUTION: The pattern classification device comprises: a preprocessing part which generates an eigen vector set common for identity classes by performing main component analysis on a learning input pattern beforehand, and reconfigures an orthogonal vector from the input pattern and the eigen vector set; a high-dimensional vector conversion part which converts the orthogonal vector into a high-dimensional vector by multiple linear mapping (tensor product); a high-dimensional partial space similarity calculation part which generates out a high-dimensional eigen vector set from the high-dimensional vector for each class (k) and calculates and generates similarity for each class between the high-dimensional vector and a high-dimensional eigen vector set Ψ (k, m); and an identity classification part which performs individual identity classification from the similarity for each class.SELECTED DRAWING: Figure 1 |
