高斯小波生成与给定频率-地球科学堆栈交换江南电子竞技平台江南体育网页版
最近30从www.hoelymoley.com
2023 - 07 - 10 - t06:01:39z
//www.hoelymoley.com/feeds/question/7463
https://creativecommons.org/licenses/by-sa/4.0/rdf
//www.hoelymoley.com/q/7463
5
高斯小波生成与给定频率
阿玛蒂亚
//www.hoelymoley.com/users/5413
2016 - 02年- 05 - t07:13:07z
2016 - 02 - 16 - t13:38:06z
< p >我如何生成一个高斯小波(时间域)与给定的中心频率。< / p > < p >我的意思是如果我做傅里叶变换频谱应该在给定的中心频率而不是零。例如谱的峰值是20 hz及其旁瓣变得几乎为零20 \ pm 10美元左右。< / p > < p >我几个编码进行锻炼,我试着在这里。< a href = " https://stackoverflow.com/questions/35211841/gaussian-wave-generation-with-a-given-central-frequency " > < / > < / p >链接
//www.hoelymoley.com/questions/7463/-/7465 # 7465
2
答案由马特·霍尔高斯小波生成与给定频率
马特·霍尔
//www.hoelymoley.com/users/28050
2016 - 02年- 05 - t11:05:17z
2016 - 02年- 05 - t11:05:17z
< p >如果我理解这个问题,我不认为你可以做你想做的事情。高斯时间序列的谱频率必须包含< a href = " https://en.wikipedia.org/wiki/DC_bias " rel = " nofollow noreferrer " >直流< / >,即非常低的频率(Python代码< a href = " http://docs.scipy.org/doc/scipy-0.16.1/reference/generated/scipy.signal.gaussian.html " rel = " nofollow noreferrer " >从scipy.org < / >): < / p > < p > < a href = " https://i.stack.imgur.com/5naUK.png " rel = " nofollow noreferrer " > < img src = " https://i.stack.imgur.com/5naUK.png " alt =“高斯谱”> < / > < / p > < p > < em >的子波频谱< / em >是一个高斯称为< a href = " http://subsurfwiki.org/wiki/Ricker_wavelet " rel = " nofollow noreferrer " >雷克子波< / >,或者有时墨西哥帽小波。我经常使用这个小波模型< a href = " https://en.wikipedia.org/wiki/Reflection_seismology " rel = " nofollow noreferrer " > < / >地震反射数据。它有一个中心频率、带宽受限。因此,小波在零附近振荡振幅-它没有直流分量:< / p > < p > < a href = " https://i.stack.imgur.com/ugW58.png " rel = " nofollow noreferrer " > < img src = " https://i.stack.imgur.com/ugW58.png " alt = "雷克子波" > < / > < / p >
//www.hoelymoley.com/questions/7463/-/7515 # 7515
2
答案由安东尼奥·高斯小波生成与给定频率
安东尼奥
//www.hoelymoley.com/users/4636
2016 - 02 - 16 - t13:34:41z
2016 - 02 - 16 - t13:34:41z
< p > Amartya, < / p > < p >也许这将有助于澄清:< / p > < p >在时域卷积等价于乘法在频域。这是我们如何构建简单的卷积震动图。< / p > < p > s (t) = w (t) * r (t) = > s (f) = w (f) r (f) < / p > < p > < a href = " https://i.stack.imgur.com/gOhgw.png " rel = " nofollow noreferrer " > < img src = " https://i.stack.imgur.com/gOhgw.png " alt = "在这里输入图像描述" > < / > < / p > < p >然而,你正在试图做的是几乎完全相反。一个正弦信号在时域频域。和你正在试图做的是“卷积”高斯的飙升,在频域。但同样的规则适用于另一种方法:在频域卷积等价于在时间域乘法。< / p > < p > S (f) = W (f) * R (f) = > S (t) = W (t) R (t) < / p > < p > < a href = " https://i.stack.imgur.com/mXu3O.png " rel = " nofollow noreferrer " > < img src = " https://i.stack.imgur.com/mXu3O.png " alt = "在这里输入图像描述" > < / > < / p > < p >为了得到小波(时间)的傅里叶变换是一个高斯分布集中在某一个频率,您将需要特定频率的正弦信号乘以一个高斯窗口(时间)。这种“高斯乘以一个正弦信号”被称为Morlet小波(或伽柏小波在EE)。< / p > < pre > <代码>元= 500;%你的样本数量小波dt = 0.001;在时间t = dt * %采样率((1:nt)装天花板(nt / 2) '; % Time vector for wavelet symmetric around zero sinusoid=cos(2*pi*fdom.*t+phase); % Sinusoid of desired frequency and phase win=exp(-(1*t*fdom).^2); % Gaussian window appropriate for dominant frequency wav=win.*sinusoid; % Final Morlet wavelet Hope this helps,
Antonio
//www.hoelymoley.com/questions/7463/-/7516 # 7516
1
答案由安东尼奥·高斯小波生成与给定频率
安东尼奥
//www.hoelymoley.com/users/4636
2016 - 02 - 16 - t13:38:06z
2016 - 02 - 16 - t13:38:06z
双柱< p >(对不起,有一个图片限制)< / p > < p >,当你使高斯窗(及时)的苗条和苗条(“1”的通过改变窗口函数),你将高斯函数在频域越来越广泛,根据傅里叶不确定性原理。< / p > < p > < a href = " https://i.stack.imgur.com/iJDaf.png " rel = " nofollow noreferrer " > < img src = " https://i.stack.imgur.com/iJDaf.png " alt = "在这里输入图像描述" > < / > < / p > < p >最后,我只是想指出,雷克子波没有高斯振幅谱。这是接近但不完全。堆垛机的振幅谱略有倾斜。他们似乎使用雷克小波在你引用的论文。< / p > < p > < a href = " https://i.stack.imgur.com/OtfCp.png " rel = " nofollow noreferrer " > < img src = " https://i.stack.imgur.com/OtfCp.png " alt = "在这里输入图像描述" > < / > < / p > < p >好吧现在我完成了。好运！< / p > < br >安东尼奥