The complexity of Boolean networks
The complexity of Boolean networks
Minimum disclosure proofs of knowledge
Journal of Computer and System Sciences - 27th IEEE Conference on Foundations of Computer Science October 27-29, 1986
Completeness theorems for non-cryptographic fault-tolerant distributed computation
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
Multiparty unconditionally secure protocols
STOC '88 Proceedings of the twentieth annual ACM symposium on Theory of computing
A discrete logarithm implementation of perfect zero-knowledge blobs
Journal of Cryptology
The multiplicative complexity of quadratic boolean forms
Theoretical Computer Science
On the multiplicative complexity of Boolean functions over the basis ∧,⊕,1
Theoretical Computer Science - Selected papers in honor of Manuel Blum
Concrete Mathematics: A Foundation for Computer Science
Concrete Mathematics: A Foundation for Computer Science
The Multiplicative Complexity of Boolean Functions
AAECC-6 Proceedings of the 6th International Conference, on Applied Algebra, Algebraic Algorithms and Error-Correcting Codes
A 2.5 n-lower bound on the combinational complexity of Boolean functions
STOC '75 Proceedings of seventh annual ACM symposium on Theory of computing
ASIACRYPT'05 Proceedings of the 11th international conference on Theory and Application of Cryptology and Information Security
An elementary proof of a 3n - o(n) lower bound on the circuit complexity of affine dispersers
MFCS'11 Proceedings of the 36th international conference on Mathematical foundations of computer science
A new combinational logic minimization technique with applications to cryptology
SEA'10 Proceedings of the 9th international conference on Experimental Algorithms
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The multiplicative complexity of a Boolean function f is defined as the minimum number of binary conjunction (AND) gates required to construct a circuit representing f, when only exclusive-or, conjunction and negation gates may be used. This article explores in detail the multiplicative complexity of symmetric Boolean functions. New techniques that allow such exploration are introduced. They are powerful enough to give exact multiplicative complexities for several classes of symmetric functions. In particular, the multiplicative complexity of computing the Hamming weight of n bits is shown to be exactly n-H^N(n), where H^N(n) is the Hamming weight of the binary representation of n. We also show a close relationship between the complexities of basic symmetric functions and the fractal known as Sierpinski's gasket.