寻找最小数的matlab代码-fips-sp800-90b-matlab:Matlab实施NISTSP800-90B统计测试(2018年1月版

上传者: 38746515 | 上传时间: 2025-04-10 22:19:55 | 文件大小: 97KB | 文件类型: ZIP
寻找最小数的matlab代码自述文件,2018年7月30日。 版权所有Crypto4A Technologies Inc.2018 介绍 该目录包含一组Matlab函数,以帮助表征NIST SP800-90B(2018年1月)中介绍的噪声源的熵。 SP800-90B文档中描述的每个IID测试,包括附加的卡方函数和每个最小熵估计,都已在Matlab中实现,并使用二进制数据进行了测试。 此外,还提供了一种快速(尽管不够精确)的测试来确定数据集是否为IID。 读者可以参考NIST的SP800-90B文档(),以获得有关此存储库中实施的统计测试的更多详细信息。 请注意,本文档中“ xyz部分”的每次使用均指代SP800-90B中相同名称的部分。 有关如何使用这些工具的指针: 获得Matlab和工具集的“测试过”版本(其他版本尚未经过测试): Matlab 2018a,distrib_computing_toolbox和statistics_toolbox。 如果要使用功能read_bin_files和independance_test_binary ,则还需要通讯系统工具箱具有bi2de和de

文件下载

资源详情

[{"title":"( 50 个子文件 97KB ) 寻找最小数的matlab代码-fips-sp800-90b-matlab:Matlab实施NISTSP800-90B统计测试(2018年1月版","children":[{"title":"fips-sp800-90b-matlab-master","children":[{"title":"setup.m <span style='color:#111;'> 1.61KB </span>","children":null,"spread":false},{"title":"precalculated_std_deviations.csv <span style='color:#111;'> 6.60KB </span>","children":null,"spread":false},{"title":"Helpful_functions","children":[{"title":"finding_bounds.m <span style='color:#111;'> 3.02KB </span>","children":null,"spread":false},{"title":"findfiles.m <span style='color:#111;'> 3.30KB </span>","children":null,"spread":false},{"title":"measure_lrs.m <span style='color:#111;'> 5.68KB </span>","children":null,"spread":false},{"title":"convert1.m <span style='color:#111;'> 2.70KB </span>","children":null,"spread":false},{"title":"Shuffle.m <span style='color:#111;'> 2.21KB </span>","children":null,"spread":false},{"title":"read_bin_file.m <span style='color:#111;'> 1.90KB </span>","children":null,"spread":false},{"title":"convert2.m <span style='color:#111;'> 2.78KB </span>","children":null,"spread":false},{"title":"getkey.m <span style='color:#111;'> 5.20KB </span>","children":null,"spread":false},{"title":"fast_Q_filling.m <span style='color:#111;'> 1.79KB </span>","children":null,"spread":false},{"title":"lagrange_interpolation.m <span style='color:#111;'> 2.34KB </span>","children":null,"spread":false},{"title":"get_lrs_length.m <span style='color:#111;'> 3.26KB </span>","children":null,"spread":false},{"title":"G.m <span style='color:#111;'> 2.42KB </span>","children":null,"spread":false},{"title":"find_repeated_str.m <span style='color:#111;'> 3.75KB </span>","children":null,"spread":false},{"title":"get_data.m <span style='color:#111;'> 8.21KB </span>","children":null,"spread":false},{"title":"x_function.m <span style='color:#111;'> 2.05KB </span>","children":null,"spread":false}],"spread":false},{"title":"LICENSE <span style='color:#111;'> 1.04KB </span>","children":null,"spread":false},{"title":"Estimating_min_entropy","children":[{"title":"lag_prediction_estimate.m <span style='color:#111;'> 4.55KB </span>","children":null,"spread":false},{"title":"collision_estimate.m <span style='color:#111;'> 3.17KB </span>","children":null,"spread":false},{"title":"lrs_estimate.m <span style='color:#111;'> 4.98KB </span>","children":null,"spread":false},{"title":"markov_estimate.m <span style='color:#111;'> 3.11KB </span>","children":null,"spread":false},{"title":"multimcw_estimate.m <span style='color:#111;'> 6.09KB </span>","children":null,"spread":false},{"title":"all_estimates.m <span style='color:#111;'> 6.53KB </span>","children":null,"spread":false},{"title":"t_tuple_estimate.m <span style='color:#111;'> 3.55KB </span>","children":null,"spread":false},{"title":"compression_estimate.m <span style='color:#111;'> 3.72KB </span>","children":null,"spread":false},{"title":"lz78y_prediction_estimate.m <span style='color:#111;'> 6.63KB </span>","children":null,"spread":false},{"title":"multimmc_prediction_estimate.m <span style='color:#111;'> 7.15KB </span>","children":null,"spread":false},{"title":"most_common_value_estimate.m <span style='color:#111;'> 1.91KB </span>","children":null,"spread":false}],"spread":false},{"title":"README.md <span style='color:#111;'> 14.16KB </span>","children":null,"spread":false},{"title":"Testing_IID_assumption","children":[{"title":"Fast_IID_testing_assumption","children":[{"title":"fast_test_IID_assumption.m <span style='color:#111;'> 5.77KB </span>","children":null,"spread":false},{"title":"fast_IID_test_runner.m <span style='color:#111;'> 16.78KB </span>","children":null,"spread":false}],"spread":true},{"title":"Chi_square_tests","children":[{"title":"independance_test_binary.m <span style='color:#111;'> 3.15KB </span>","children":null,"spread":false},{"title":"goodness_of_fit_test_binary.m <span style='color:#111;'> 2.47KB </span>","children":null,"spread":false},{"title":"lrs_test.m <span style='color:#111;'> 3.99KB </span>","children":null,"spread":false}],"spread":true},{"title":"IID_testing_assumption","children":[{"title":"compression_test.m <span style='color:#111;'> 2.09KB </span>","children":null,"spread":false},{"title":"run_test.m <span style='color:#111;'> 2.41KB </span>","children":null,"spread":false},{"title":"length_test.m <span style='color:#111;'> 2.88KB </span>","children":null,"spread":false},{"title":"avg_collision_test.m <span style='color:#111;'> 2.99KB </span>","children":null,"spread":false},{"title":"excursion_test.m <span style='color:#111;'> 2.18KB </span>","children":null,"spread":false},{"title":"covariance_test.m <span style='color:#111;'> 2.10KB </span>","children":null,"spread":false},{"title":"periodicity_test.m <span style='color:#111;'> 2.22KB </span>","children":null,"spread":false},{"title":"incdec_test.m <span style='color:#111;'> 2.51KB </span>","children":null,"spread":false},{"title":"test_IID_assumption.m <span style='color:#111;'> 5.30KB </span>","children":null,"spread":false},{"title":"max_collision_test.m <span style='color:#111;'> 2.94KB </span>","children":null,"spread":false},{"title":"length_median_test.m <span style='color:#111;'> 2.63KB </span>","children":null,"spread":false},{"title":"run_median_test.m <span style='color:#111;'> 2.42KB </span>","children":null,"spread":false}],"spread":false},{"title":"approximation_IID_testing.m <span style='color:#111;'> 7.18KB </span>","children":null,"spread":false}],"spread":true},{"title":"automated_tests.m <span style='color:#111;'> 4.44KB </span>","children":null,"spread":false},{"title":"precalculated_averages.csv <span style='color:#111;'> 4.51KB </span>","children":null,"spread":false}],"spread":true}],"spread":true}]

评论信息

免责申明

【只为小站】的资源来自网友分享,仅供学习研究,请务必在下载后24小时内给予删除,不得用于其他任何用途,否则后果自负。基于互联网的特殊性,【只为小站】 无法对用户传输的作品、信息、内容的权属或合法性、合规性、真实性、科学性、完整权、有效性等进行实质审查;无论 【只为小站】 经营者是否已进行审查,用户均应自行承担因其传输的作品、信息、内容而可能或已经产生的侵权或权属纠纷等法律责任。
本站所有资源不代表本站的观点或立场,基于网友分享,根据中国法律《信息网络传播权保护条例》第二十二条之规定,若资源存在侵权或相关问题请联系本站客服人员,zhiweidada#qq.com,请把#换成@,本站将给予最大的支持与配合,做到及时反馈和处理。关于更多版权及免责申明参见 版权及免责申明