fft

Matlab FFT (Fast Fourier Transform) function of non log-base2 numbers

点点圈 提交于 2019-12-11 11:55:51
问题 I have an app that I am developing that utalizes Apple's Accelerate Framework FFT function and I am trying to make it mimic the functionality of Matlab's FFT function. I have my current code set up to output exactly the same way as I am doing so in matlab. The only time that it doesn't output identically is when the number of elements in the data array are != a logarithm of base 2 (technically necessary for an FFT). I was wondering if anyone knew how the Matlab Function handled this case. If

Detecting Seasonality in R

自古美人都是妖i 提交于 2019-12-11 11:15:31
问题 Problem: Detecting cyclical patterns in daily data using periodogram and FFT in R. The issue is how to code in R the periodogram to detect monthly, quarterly, semi-annual, annual..etc cyclical patterns in the data. In other words I need to detect the existence of cyclical patterns for low frequencies ( ie: 1 year=> 2*pi/365, 6 months = > 4*pi/365, etc) Reproducible Example: library(weatherData) w2009=getWeatherForYear("sfo",2009) w2010=getWeatherForYear("sfo",2010) w2011=getWeatherForYear(

FFT in Excel — How to Obtain the Most Realistic Spectrum

空扰寡人 提交于 2019-12-11 11:06:40
问题 I’m trying to obtain the FFT spectrum of these data: gggttt.host.sk/sample.xls using Excel. @Paul R helped me a lot in another question to figure out the meaning of bins but there are still questions which I’d like to understand. First, Excel, even when the moduli are represented in log scale, does not show them in dB. What do you do to have these magnitudes converted to dB? Further, there’s a concern about the window function, aliasing etc. Since I’m crunching data from exactly one period,

How to convert spectral density to amplitude

喜你入骨 提交于 2019-12-11 10:29:40
问题 I have standard periodogram produced from the spectrum function call in the R "stats" package. It produces a spectral density on the Y axis. I wish to actually inspect the amplitude of the key frequency signals. How do i convert the spectral density to an amplitude? Is there a periodgram plot/analysis in R that produces a frequency vs amplitude plot automatically? Appreciate any advice. 回答1: Maybe you use different terminology than I do. The help page says that value returned from the

luogu P5488 差分与前缀和 FFT

ぐ巨炮叔叔 提交于 2019-12-11 10:27:56
又是一道FFT 好题。 首先来看一看求前缀和。 求一次前缀和就先当于卷上一个系数全为1的多项式,即 \(\displaystyle \sum_{i=0}^{\infin}x^i\) ( 想一想,为什么 ),这个东西就等于 \(\displaystyle \frac{1}{1-x}\) ,简单证明一下。 \[ S=1+x+x^2+...\\ xS=x+x^2+x^3...\\ 上边的式子减去下边的式子得到\\ S-xS=1\\ S=\frac{1}{1-x} \] 是不是感觉天衣无缝但又十分扯淡?没错,这只有在 \(-1<x<1\) 时才成立。但生成函数是形式幂级数,我们不用关心x的具体取值。 回到我们刚才的问题,因为卷积具有结合律,所以我们要求的就是 \(\displaystyle\frac{1}{(1-x)^k}\) 结论:这个式子的n次系数是 \(C_{n+k-1}^{k-1}\) (C是组合数)。 证明:回想一下 \(\displaystyle \sum_{i=0}^{\infin}x^i\) 的每一次相乘的含义,可知 \(\displaystyle (\sum_{i=0}^{\infin}x^i)^k\) 中n次系数的含义就是经过k次组成n的方案数,我们可以将n看成是n个小球,k看成是k个盒子,因为组成n的每个 “1”是一样的,每个多项式是不一样的,所以球相同,盒子不同

FFT/NTT基础题总结

柔情痞子 提交于 2019-12-11 09:01:09
在学各种数各种反演之前把以前做的$FFT$/$NTT$的题整理一遍 还请数论$dalao$口下留情 T1快速傅立叶之二 题目中要求求出 $c_k=\sum\limits_{i=k}^{n-1}a_i*b_{i-k}$ 首先可以把$a$翻转, $c_k=\sum\limits_{i=k}^{n-1}a_{n-1-i}*b_{i-k}$ $c_k=\sum\limits_{i=0}^{n-k-1}a_{n-k-1-i}*b_{i}$ 也就是说对新的$a$,$b$数组做一遍$FFT$得到的便是$c$数组翻转后的数组 T2力 $f[i]=\sum_{j=1}^{i-1}\frac{q[j]}{(i-j)^2}-\sum_{j=i+1}^{n}\frac{q[j]}{(i-j)^2}$ $f[i]=\sum_{k=1}^{min(n-i,i-1)}\frac{q[j-k]-q[j+k]}{k^2}$ 构造出一个$g[i]=\frac{1}{i^2}$就是一个裸的卷积了 T3Normal 因为期望的可加性,把每个点的贡献单独处理,即求期望深度 考虑$y$对$x$的贡献:当且仅当$x->y$的路径上第一个点就选$y$,$y$才能成为$x$的祖先 所以$y$对$x$的贡献就是:$P=\frac{1}{dis(x,y)+1}$,$E=1$ 所以最终答案就是$\sum\limits_{i=1}^{n}

luogu P4173 残缺的字符串 FFT

主宰稳场 提交于 2019-12-11 08:11:25
温馨提示:倘若下角标看不清的话您可以尝试放大。 倘若没有通配符的话可以用KMP搞一搞。 听巨佬说通配符可以用FFT搞一搞。 我们先考虑一下没有通配符的怎么搞。我们设a=1,b=2,...,然后我们构造一个这样的函数 \(\displaystyle P_x=\sum_{i=0}^{m-1}(A_i-B_{x-m+1+i})^2\) ,但且仅当A和B在x的位置上匹配完成的时候$P_x $为0。至于为什么是平方,主要是为了防止正数和负数相互抵消。 至于通配符,我们设它为0,我们尝试重新构造一下 \(\displaystyle P_x=\sum_{i=0}^{m-1}(A_i-B_{x-m+1+i})^2A_iB_{x-m+1+i}\) ,这样我们就能满足"通配"这一条件了。 那我们怎么快速求解呢?我们将式子先展开一下, \(\displaystyle P_x=\sum_{i=0}^{m-1}(A_i^3B_{x-m+1+i}-A_i^2B_{x-m+1+i}^2+A_iB_{x-m+1+i}^3)\) \(\displaystyle=\sum_{i=0}^{m-1}A_i^3B_{x-m+1+i}-\sum_{i=0}^{m-1}A_i^2B_{x-m+1+i}^2+\sum_{i=0}^{m-1}A_iB_{x-m+1+i}^3\) 还是老方法,我们尝试将A翻转一下设 \(A_i=C_

Numpy's FFT with Intel MKL

左心房为你撑大大i 提交于 2019-12-11 07:38:11
问题 Running numpy.fft.fft(np.eye(9),norm="ortho) leads to TypeError: fft() got an unexpected keyword argument 'norm' . I am running Numpy with Intel MKL. Could it be that there is something wrong with the linkings inside the libraries? 来源: https://stackoverflow.com/questions/38786227/numpys-fft-with-intel-mkl

Accelerate framework vDSP, FFT framing

懵懂的女人 提交于 2019-12-11 07:15:52
问题 I'm trying to implement FFT calculation, using Apple's vDSP, on a recorded audio file (let's assume it's a mono PCM). I've did a research here and I've found following topics quite useful: Using the apple FFT and accelerate Framework Extracting precise frequencies from FFT Bins using phase change between frames Reading audio with Extended Audio File Services (ExtAudioFileRead) For example, we configured FFT with frame_size N = 1024 samples, log2n=10: m_setupReal = vDSP_create_fftsetup(LOG_2N,

Why doesn't FFT automatically produce a zero-frequency centered output?

蹲街弑〆低调 提交于 2019-12-11 06:52:20
问题 There is an operation called Shift which is performed after DFT to bring zero-frequency components to the center of the frequency spectrum. I have two questions regarding this operation: Why don't/can't DFT automatically center the zero-frequency components? What happens if we don't perform Shift operation after DFT? I.e. how does it affect our other tasks of image processing? Can anyone provide me some material to know about this specific operation named Shift ? References: - fftw shift zero