Discrete neural computation: a theoretical foundation
Discrete neural computation: a theoretical foundation
On the computational power of threshold circuits with sparse activity
Neural Computation
Theoretical Computer Science
Size and Energy of Threshold Circuits Computing Mod Functions
MFCS '09 Proceedings of the 34th International Symposium on Mathematical Foundations of Computer Science 2009
Energy complexity and depth of threshold circuits
FCT'09 Proceedings of the 17th international conference on Fundamentals of computation theory
Energy and fan-in of threshold circuits computing mod functions
TAMC'11 Proceedings of the 8th annual conference on Theory and applications of models of computation
Lower bounds for linear decision trees via an energy complexity argument
MFCS'11 Proceedings of the 36th international conference on Mathematical foundations of computer science
Energy and fan-in of logic circuits computing symmetric Boolean functions
Theoretical Computer Science
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We prove that the modulus function MODm of n variables can be computed by a threshold circuit C of energy e and size s = O(e(n/m)1/(e−1)) for any integer e ≥ 2, where the energy e is defined to be the maximum number of gates outputting "1" over all inputs to C, and the size s to be the number of gates in C. Our upper bound on the size s almost matches the known lower bound s = Ω(e(n/m)1/e).