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Random Number Generation and Dynamical System : Statistical Properties of Binary Sequences Generated by One-dimensional Maps (5th Workshop on Stochastic Numerics)

机译：随机数生成和动力学系统：一维图生成的二进制序列的统计特性（第五届随机数字研讨会）

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Oohama Yasutada; Kohda Tohru;
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年度 2001
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1. Statistical Properties of Chaotic Binary Sequences Generated by One-Dimensional Maps [J] . Yasutada OOHAMA, Tohru KOHDA IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences . 2002,第9期

机译：一维映射生成的混沌二元序列的统计性质
2. Design of binary sequences with tunable exponential autocorrelations and run statistics based on one-dimensional chaotic maps [J] . Tsuneda A. IEEE transactions on circuits and systems . I , Regular papers . 2005,第2期

机译：基于一维混沌映射的具有可调指数自相关和运行统计的二进制序列设计
3. Design of Binary Sequences With Tunable Exponential Autocorrelations and Run Statistics Based on One-Dimensional Chaotic Maps [J] . Akio Tsuneda IEEE Transactions on Circuits and Systems. 1, Fundamental Theory and Applications . 2005,第2期

机译：基于一维混沌映射的具有指数自相关和游程统计的二进制序列设计
4. On auto-correlation properties of chaotic binary sequences generated by one-dimensional maps [C] . Akio Tsuneda Conference of the IEEE Industrial Electronics Society, Annual . 2000

机译：一维地图生成的混沌二进制序列的自相关属性
5. Statistical properties of pseudorandom sequences. [D] . Gu, Ting. 2016

机译：伪随机序列的统计特性。
6. Statistical properties of cerebral CT perfusion imaging systems. Part I. Cerebral blood volume maps generated from nondeconvolution-based systems [O] . Ke Li, Charles M. Strother, Guang-Hong Chen -1

机译：脑CT灌注成像系统的统计特性。第一部分：从基于非反卷积的系统生成的脑血容量图
7. Statistical Properties of Real-Valued Sequences Generated by Chebyshev maps (5th Workshop on Stochastic Numerics) [O] . Fujisaki Hiroshi 2001

机译：Chebyshev映射生成的实值序列的统计特性（第五届随机数字研讨会）
8. The simultaneous use of several pseudo-random binary sequences in the identification of linear multivariable dynamic systems [R] . J. D. Cummins 1965

机译：在线性多变量动态系统的识别中同时使用几个伪随机二进制序列

Random Number Generation and Dynamical System : Statistical Properties of Binary Sequences Generated by One-dimensional Maps (5th Workshop on Stochastic Numerics)

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