Reduction of the storage requirements of Bledsoe and Browning's n-tuple method of pattern recognition

摘要

Random superimposed coding has reduced the massive storage requirements of the Bledsoe and Browning Method of Pattern Recognition, applied to unconstrained hand-printed numerals with n = 14, by a factor of roughly four. A fourfold reduction in storage area can also be achieved by the use of associative memory, but at higher cost per bit. A third approach aims to achieve economy by exploiting any non-randomness of stored n-tuple states, but this is discussed only in outline.