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Another example from the same sieve is depicted in Fig. 6.9 for ID = 5315 and
may be regarded as an example of emerging self-reproductive patterns. This is not
a case of trivial self-reproduction as in the case of Fredkin genes (as for ID = 300
and ID = 682 of the “2s5” family in Chap. 5, Fig. 5.7 and 5.8) but rather a much
more complex phenomenon. When enough such self-reproductive patterns occur
during the finite array, the process stops. Further studies of such self-reproductive
patterns may reveal very interesting computational properties.
Another interesting example revealed by the sieve is cell ID = 6216 (see
Fig. 6.10) with its associated CAs exhibiting a dynamic similar to that of the
“Game of Life” (ID = 6152).
6.3.4 Sieves to Locate Feature Extractors
In the next another set of sieves is introduced, with some practical relevance
in various pattern recognition problems. Experimental simulations indicate that
“imploding” behaviors with a low exponent of growth may be used as feature
extractors. It is also assumed that the more complex is the nature of the signal
processing the larger is the transient parameter. Therefore a sieve for pattern
extraction may be defined as in Fig. 6.11. It is interesting to note that the “Game
of Life” cell popped-out from this sieve as well. This clearly indicates that besides
feature extraction, universal computation (as a result of glider collision) may be
also found among the cells selected by this sieve.
Fig. 6.11. Double sieve for identifying feature extractors or universal cellular universal
computers
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