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.
