A cycle in GF(2**4) generated by alpha=(x**4+x+1). It is extended an extra 16 entries to avoid some expensive mod operations.翻译
时间: 2024-04-24 07:21:34 浏览: 18
在 GF(2**4) 中,由 alpha=(x**4+x+1) 生成的循环。为了避免一些昂贵的模操作,它被扩展了额外的 16 个条目。
GF(2**4) 是一个有限域,其中的元素是二进制多项式。alpha=(x**4+x+1) 是一个生成元,它可以用来生成 GF(2**4) 中的所有元素。循环是指通过连续应用 alpha 的乘法运算,得到的一系列元素。
为了提高计算效率,循环被扩展了额外的 16 个条目。这样,在进行乘法运算时,可以直接使用循环中对应位置的元素,而无需进行昂贵的模操作。这种技巧可以减少计算的复杂性和运行时间。
请注意,这段翻译仅仅解释了给定句子的含义,具体的细节和应用可能需要更多的上下文信息和背景知识。
相关问题
y_data = 9.0 * x_data + 2.0 * x_data + 8.0 * x_data + 1.0 + np.random.randn( *x_data.shape) * 0.4
This code is not complete and contains errors. It appears to be attempting to create a set of y values based on a set of x values. However, it is not clear what the intended operation is for each term in the equation.
Here is an example of how the code could be rewritten to create a set of y values that are a combination of the x values and some random noise:
```
import numpy as np
x_data = np.linspace(-10, 10, 100)
noise = np.random.randn(*x_data.shape) * 0.4
y_data = 9.0 * x_data + 2.0 * x_data - 8.0 * x_data + 1.0 + noise
```
In this version, the y values are created by multiplying the x values by some constants (9.0, 2.0, and -8.0), adding a constant term (1.0), and adding some random noise. The noise is generated using the `numpy.random.randn()` function, which creates an array of random numbers with a normal distribution. The `*x_data.shape` syntax is used to ensure that the noise array has the same shape as the x data.
state = ps*np.random.randint(1,2, size=(N,N))
As an AI language model, I am not sure about the context and the meaning of the variables used in the code snippet. However, I can explain the syntax and the possible outcome of the code.
The code creates a NumPy array called "state" with dimensions N x N, where N is the size of the square grid. The values in the array are randomly generated integers between 1 and 2, inclusive, multiplied by a variable "ps". The value of "ps" is not defined in the code snippet.
The outcome of the code depends on the value of "ps" and the size of the grid. Since the range of the random integers is limited to 1 and 2, the array will mostly consist of either 1 or 2 values multiplied by "ps". The specific pattern of the array will be random and depend on the random number generator used by NumPy.
Overall, the purpose and the behavior of the code is not clear without additional context.