Reduction of the storage requirements of Bledsoe and Browning's n-tuple method of pattern recognition
作者： J.R. Ullmann
DOI: 10.1016/0031-3203(71)90019-7
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摘要: Abstract Random superimposed coding has reduced the massive storage requirements of Bledsoe and Browning Method Pattern Recognition, applied to unconstrained hand-printed numerals with n = 14, by a factor roughly four. A fourfold reduction in area can also be achieved use associative memory, but at higher cost per bit. third approach aims achieve economy exploiting any non-randomness stored -tuple states, this is discussed only outline.
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