Patent ID: 11687554

Abstract:
An embodiment of the present invention is provided with a projective transform model including a plurality of nodes and a projection table, the plurality of nodes each holding a reference vector having a dimension corresponding to the dimension of multi-dimensional data. The projection table indicates the correspondence relation between the number of each node and a coordinate in a two-dimensional space as a projection target of the reference vector held by the node. First in a learning phase, multi-dimensional input data of a positive example and a negative example is acquired, the amplitude characteristic amounts thereof are calculated, and this amplitude characteristic amount data is learned as the reference vectors of the nodes for each sample. Subsequently, the Euclidean distance between coordinates when the nodes learned based on the amplitude characteristic amount data of the positive example and the nodes learned based on the amplitude characteristic amount data of the negative example are projected into the two-dimensional space in accordance with the projection table is calculated, and coordinates in the projection table are updated so that the calculated Euclidean distance becomes equal to or larger than a threshold value.