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dc.contributor.authorGofford, David K.en_US
dc.date.accessioned2023-03-29T14:32:24Z
dc.date.available2023-03-29T14:32:24Z
dc.date.issued1988-09
dc.identifier.urihttps://hdl.handle.net/1721.1/149144
dc.description.abstractWe present a method for generaing random numbers from natural noise sources that is able to produce random numbers to any desired level of perfection. The method works by transducing a physical noise source to generate a stream of biased natural bits, and then applying an unbiasing algorithm. The Wiener-Kinchine relation is used to derive the autocorrelation present in the stream of biased bits and to define safe sampling rate. Experimental results from an implementation of our method support our analysis. One consequence of our analysis is that a broad class of natural random number generators, including ours, can not generate absolutely perfect random numbers.en_US
dc.relation.ispartofseriesMIT-LCS-TM-371
dc.titleNatural Random Numbersen_US
dc.identifier.oclc20300043


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