A catalog of complexity classes
Handbook of theoretical computer science (vol. A)
Circuit complexity and neural networks
Circuit complexity and neural networks
Discrete neural computation: a theoretical foundation
Discrete neural computation: a theoretical foundation
On the computational power of threshold circuits with sparse activity
Neural Computation
Approximability of Minimum AND-Circuits
Algorithmica
Improved approximation algorithms for minimum AND-circuits problem via k-set cover
Information Processing Letters
Size-energy tradeoffs for unate circuits computing symmetric Boolean functions
Theoretical Computer Science
IEEE Transactions on Information Theory
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Let C be a logic circuit consisting of s gates g1, g2,..., gs, then the output pattern of C for an input x ε {0, 1}n is defined to be a vector (g1(x), g2(x),..., gs(x)) ∈ {0, 1}s of the outputs of g1, g2,..., gs for x. For each f: {0, 1}2 → {0, 1}, we define an f-circuit as a logic circuit where every gate computes f, and investigate computational complexity of the following counting problem: Given an f-circuit C, how many output patterns arise in C? We then provide a dichotomy result on the counting problem: We prove that the problem is solvable in polynomial time if f is PARITY or any degenerate function, while the problem is #P-complete even for constant-depth f-circuits if f is one of the other functions, such as AND, OR, NAND and NOR.