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Patent Title: Visualization and self organization of multi-dimensional data through equalized orthogonal mapping

Assignee: Computer Associates International, Inc.
Patent Number: US6907412
Issue Date: 06-14-2005
Application Number:
File Date:03-23-2001

Abstract: The subject system provides reduced-dimension mapping of pattern data. Mapping is applied through conventional single-hidden-layer feed-forward neural network with non-linear neurons. According to one aspect of the present invention, the system functions to equalize and orthogonalize lower dimensional output signals by reducing the covariance matrix of the output signals to the form of a diagonal matrix or constant times the identity matrix. The present invention allows for visualization of large bodies of complex multidimensional data in a relatively "topologically correct" low-dimension approximation, to reduce randomness associated with other methods of similar purposes, and to keep the mapping computationally efficient at the same time.


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