问题描述
我想知道numpy/scipy中是否有用于1d数组圆形卷积的函数. scipy.signal.convolve()
函数仅提供模式",而不是边界",而signal.convolve2d()
函数需要2d数组作为输入.
I wonder if there's a function in numpy/scipy for 1d array circular convolution. The scipy.signal.convolve()
function only provides "mode" but not "boundary", while the signal.convolve2d()
function needs 2d array as input.
作为时间序列作业的一部分,我需要这样做以比较开放卷积与圆形卷积.
I need to do this to compare open vs circular convolution as part of a time series homework.
推荐答案
由于这是用于家庭作业,因此我省略了一些细节.
Since this is for homework, I'm leaving out a few details.
如果您附加了信号 a 卷积的定义. /em>本身,则 aa 和 b 之间的卷积将包含在 a 和 b .
By the definition of convolution, if you append a signal a to itself, then the convolution between aa and b will contain inside the cyclic convolution of a and b.
例如,考虑以下事项:
import numpy as np
from scipy import signal
%pylab inline
a = np.array([1] * 10)
b = np.array([1] * 10)
plot(signal.convolve(a, b));
这是标准卷积.现在,这个
That is the standard convolution. Now this, however
plot(signal.convolve(a, np.concatenate((b, b))));
在最后一个图中,尝试查看圆形卷积的结果在哪里,以及如何对其进行概括.
In this last figure, try to see where is the result of the circular convolution, and how to generalize this.
这篇关于Python:一维数组循环卷积的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!