From 96f40e293b394b11bc203ac6ba1d971b2993c3b1 Mon Sep 17 00:00:00 2001 From: c7w Date: Sun, 15 May 2022 23:01:39 +0800 Subject: [PATCH] Update readme.md --- readme.md | 10 +++++++--- readme.pdf | Bin 1021163 -> 1021535 bytes 2 files changed, 7 insertions(+), 3 deletions(-) diff --git a/readme.md b/readme.md index a8ebbac..91164e0 100644 --- a/readme.md +++ b/readme.md @@ -149,7 +149,7 @@ $$ #### RNN Cell -​ 每一个 RNN 神经元接受 160 个比特的串作为输入,这里将其记为 $I_i = J_{i1}J_{i2}J_{i3}J_{i4}J_{i5}$,其中 $J_{ij}$ 是一个 32 比特的串。我们令 $Q_1 \sim CS, Q_2 \sim CS$,然后令 $W_i \sim CS , 1\le i\le5$,定义 32 位乘法为将乘法结果的高 32 位与低 32 位异或: +​ 每一个 RNN 神经元接受 160 个比特的串作为输入,这里将其记为 $I_i = J_{i1}J_{i2}J_{i3}J_{i4}J_{i5}$,其中 $J_{ij}$ 是一个 32 比特的串。我们令 $Q_1 \sim CS, Q_2 \sim CS$,然后令 $W_i \sim CS , 1\le i\le5$,定义 32 位乘法为将乘法结果的高 32 位与低 32 位进行或运算: $$ F_1 \leftarrow J_{i1} \times W_1 + J_{i2} \times W_2 + J_{i3} \times W_3 + prev \\ F_2 \leftarrow J_{i4} \times W_4 + J_{i5} \times W_5 @@ -186,7 +186,7 @@ H_{7}=D_{2} \oplus D_{3} \oplus t_{1} \\ \text { where } t_{1}=C h\left(D_{1}, D_{2}, D_{3}\right) \oplus D_{4} \oplus \Sigma 1\left(D_{3}\right) \end{array}\right. $$ -​ 非线性激活层首先定义 $h_i = J_i\oplus J_{i+5}, 1\le i \le5$,其中 $J_i = W_i \times I_i$,$W_i \sim CS$,$I_i$ 是将输入的 320 比特等分成 10 份中的结果,长度为 32 比特,这里 $1 \le i \le 10$。32 位乘法定义为两数相乘结果中高 32 位与低 32 位的异或。 +​ 非线性激活层首先定义 $h_i = J_i\oplus J_{i+5}, 1\le i \le5$,其中 $J_i = W_i \times I_i$,$W_i \sim CS$,$I_i$ 是将输入的 320 比特等分成 10 份中的结果,长度为 32 比特,这里 $1 \le i \le 10$。32 位乘法定义为两数相乘结果中高 32 位与低 32 位的或运算。 ​ 然后,对这个结果的前 5 个 32 比特迭代重复 $N_r$ 次 $Cell_{5-8}$, @@ -236,7 +236,7 @@ $$ | 13 | Random Excursions Variant | 18/18$^1$ | 通过$^1$ | - | | 14 | Serial | 2/2$^1$ | 通过$^1$ | $m=\lfloor \log_2 n \rfloor -3$ | | 15 | Linear Complexity | 110/111 | 0.818179 | - | - +
Figure 4.2.1.1 NIST 测试结果
注: 1. 表示该检测度量有多个指标 @@ -261,6 +261,8 @@ $$ +
Figure 4.2.2.1 Diffusion Test
+ 定量计算 1. 改变位数的最小值 $B_{\min }=\min \left(\left\{B_{i}\right\}_{i=1, \ldots, N}\right)$ @@ -279,6 +281,8 @@ $$ image-20220514222253677 +
Figure 4.2.3.1 DSTMap Result
+ ​ 我们混沌系统采用的发生函数 $\text{DSTMap}_Q$ 可以很好地起到生成均匀分布的数据的目的。我们这里对 STMap 做了实验,取 $\mu = 1, Q=0.3$,然后对输出函数 $\text{STMap}_{0.3}$ 做傅里叶变换后得到上图,可以看出数据具有较强的随机性,满足均匀分布的条件。 diff --git a/readme.pdf b/readme.pdf index 90e904c416b494a010c742cd877bc2b7ad70b947..f41e271fd83ebd8d84e7e773513316cf0db60f20 100644 GIT binary patch delta 149758 zcmY(pV{j!*`0X3pPA0Z(+qSu5a|biov2ELv9ox1w$;7rf6U=?j|D1E{-Y>uIUeBuj z)K%T}^t!AT-K`Z33WE%T3WIKeX&Qjy;b?CefN`b)x%z(m?i0{ht2QI>K9%0^d<+&P zN;J;P_;C^lXZG(7W7PRY)aSPuqP29wh3fldW6H&fjej-I(I)*lP25)nx#=Vy^`~Di zHB6anS*YSN-km@1W#$T7SWYWcHEf{Bl%saJC5N(fcsa!&_^lB08(e=PrvAcD!aCHg zs7ZM_(C8T#y^c}1v?HPwPvJ^ms=lxfiDBZK|0W9in0lNQY6*ZGJguBDz3IN7&$57m z2S}MhIdj2iIy%w6*I}pU`swLgzLW$0SP*Bm^lPOfelA)3>!r;C*{*E>DaBu8D`CEV zT5X6&*fA3Ia*{7I%97S_4*2G~nPTIYeZ<-VdWz|!L$$i9p*Q6!H-?{EilKIvU++R? zm{^tFk+5<4A zlWvhLqFX+y`)Emdq_J**NsMgzEnFc@O*4-tcte1u8N!w(u3|fzgF_#d>V|`DOzZd_ z6eg_g_U+E4L%bHtVwke=V?3i)e`RSeK09cGznA60B*3p4Nzgu{$y47q!{oyIAoaM; zA9hrquawoG%@$@;??g79P*^ 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