
- 1 FORSYTHE, G E.; GERMOND, H. H.; HOUSEHOLDER, A. S. (Eds.) Monte Carlo methods. National Bureau of Standards Appl. Math. Series 12, U. S. Government Printing Office (1951).Google Scholar
- 2 MAYEL H. A. (Ed.) Sympo.ium on Monte Carlo Methods. John Wiley and Sons, New York (1956).Google Scholar
- 3 BROWN, G. V. monte Carlo methods. In Modern Mathematics for the Engineer, I, pp. 279-303.5cGraw-Hill Book Co., New York (1956).Google Scholar
- 4 DAvis, A.S. Markov chains as random input automata. Amer. Math. Month. 68 (1961), 264-267.Google Scholar
- 5 JUNCOS M. L. Random number generation on the BRL high-speed computing machines. Ballistic Res. Lab., Report No. 855, Aberdeen Proving Ground, Maryland (1953).Google Scholar
- 6 I.IosKMAN, J. The generation of pseudo-random numbers on a decimal calculator. J. ACM I (19554), 88-91. Google Scholar
- 7 TAUSSKY, O.; TODD, J. Generation and testing of pseudo-random numbers. In Symposium on Monte Carlo Methods, pp. 15--28, John Wiley and Sons, New York (1956).Google Scholar
- 8 JoHnsON, D.L. Generating and testing pseudo-random numbers on the IBM Type 701. Math. Tables Aids Comput. 10 (1956), 8-13.Google Scholar
- 9 BOFINGER, E.; BOFINGER, V. I. A periodic property of pseudo-random sequences. J. ACM 5 (1958), 261-265. Google Scholar
- 10 CErtTAINE, J .E . On sequences of pseudo-random numbers of maximal length. J. ACM 5 (1958), 353. Google Scholar
- 11 EDMONDS, A. R. The generation of pseudo-random numbers on electronic digital computers. Comput. J. 2 (1960), 181-185.Google Scholar
- 12 COVErOU, R. R. Serial correlation in the generation of pseudo-random numbers. J. ACM 7 (1960), 72-74. Google Scholar
- 13 ROTENBERG, A. A new pseudo-random number generator. J. ACM 7 (1960), 75-77. Google Scholar
- 14 HUEHN, H.G. A 48-bit pseudo-random number generator. Comm. ACM S (1961), 350-- 352. Google Scholar
- 15 GREENBERGER, M. Notes on a pseudo-random number generator. J. ACM 8 (1961), 163-167. Google Scholar
- 16 GooRr, R.E. An Mgorithm for integer solutions to linear programs. Princeton-IBM Math. Research Project, Teeh. Report No. 1 (1958).Google Scholar
- 17 GOMORY, R. E. All-integer programming algorithm. IBM Research Center Report RC-189 (1960).Google Scholar
- 18 GOMORY, R.E. Solving linear programming problems in integers. Proc. Syrup. on AppI. Math 10 (1960), 211-216.Google Scholar
- 19 MILLER, C. E.; TUCKER, A. W.; ZEMLIN, R.A. Integer programming formulation of traveling salesman problems. J. ACM 7 (1960), 326--329. Google Scholar
- 20 FELLER, W. An Introduction to Probability Theory and its Applications, I, p. 182. John Wiley and Sons, New York (1957).Google Scholar
Index Terms
On a Weight Distribution Problem, with Application to the Design of Stochastic Generators
Recommendations
Bit-Wise Behavior of Random Number Generators
In 1985, G. Marsaglia proposed the m-tuple test, a runs test on bits, as a test of nonrandomness of a sequence of pseudorandom integers. We try this test on the outputs from a large set of pseudorandom number generators and discuss the behavior of the ...
Estimating infinitesimal generators of stochastic systems with formal error bounds: a data-driven approach
HSCC '21: Proceedings of the 24th International Conference on Hybrid Systems: Computation and ControlIn this work, we propose a data-driven technique for a formal estimation of infinitesimal generators of continuous-time stochastic systems with unknown dynamics. In the proposed framework, we first approximate the infinitesimal generator of the solution ...






Comments