A new bias method for the optical implementation of cellular neural
networks is proposed to reduce electronic precalculation and increase
processing speed. A multiple-object joint transform correlator is
then used to realize the summation of multiple correlations resulting
from the bias method. Compared with other optical systems for
cellular neural networks, the proposed method offers the advantages of
higher processing speed, easy implementation, and
robustness. Computer simulations of the optical cellular neural
networks for edge detection and corner and horizontal line extraction
are also presented.
© 1999 Optical Society of America
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