Author_Institution :
NADA, R. Inst. of Technol., Stockholm, Sweden
Abstract :
We explore the problem of transforming n independent and identically biased {-1,1}-valued random variables, X1, ..., X n, into a single {-1,1} value, f(X1, ..., Xn ), so that this result is as unbiased as possible. In general, no function f produces a completely unbiased result. We perform the first study of the relationship between the bias b of these Xi and the rate at which f(X1, ..., Xn) can converge to an unbiased {-1,1} random variable (as n→∞)
Keywords :
Boolean functions; approximation theory; convergence of numerical methods; error analysis; random processes; Diophantine approximation; XOR function; biased source; convergence; error terms bounding; identically biased random variables; optimally unbiased bits extraction; perfectly unbiased output distributions; Arithmetic; Computer science; Random variables; Terminology;