Efficient Hamming weight comparators of binary vectors
S.J. Piestrak
Abstract
S.J. Piestrak
Abstract
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.
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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.
Key concepts: Hamming(7,4), Hamming weight, Hamming distance, Hamming code, Binary number, Hamming bound, Mathematics, Hamming graph