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Efficient Hamming weight comparators of binary vectors

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1 Author(s)
Piestrak, S.J. ; Lab. LICM, Univ. of Metz, Metz

New comparators of the Hamming weight of binary vectors built using threshold circuits are proposed. One version compares the Hamming weight of a binary vector to a fixed threshold, whereas the other compares the Hamming weights of two independent vectors. Their applications include digital neural networks, pattern matching and median/rank filters.

Published in:

Electronics Letters  (Volume:43 ,  Issue: 11 )