fft

问题 I am trying to use FFT to decode morse code, but I'm finding that when I examine the resulting frequency bin/bucket I'm interested in, the absolute value is varying quite significantly even when a constant tone is presented. This makes it impossible for me to use the rise and fall around a threshold and therefore decode audio morse. I've even tried the simple example that seems to be copied everywhere, but it also varies... I can't work out what I'm doing wrong, and my maths is not clever

问题 I am trying to use FFT to decode morse code, but I'm finding that when I examine the resulting frequency bin/bucket I'm interested in, the absolute value is varying quite significantly even when a constant tone is presented. This makes it impossible for me to use the rise and fall around a threshold and therefore decode audio morse. I've even tried the simple example that seems to be copied everywhere, but it also varies... I can't work out what I'm doing wrong, and my maths is not clever

问题 I am trying to use FFT to decode morse code, but I'm finding that when I examine the resulting frequency bin/bucket I'm interested in, the absolute value is varying quite significantly even when a constant tone is presented. This makes it impossible for me to use the rise and fall around a threshold and therefore decode audio morse. I've even tried the simple example that seems to be copied everywhere, but it also varies... I can't work out what I'm doing wrong, and my maths is not clever

问题 I am trying to use FFT to decode morse code, but I'm finding that when I examine the resulting frequency bin/bucket I'm interested in, the absolute value is varying quite significantly even when a constant tone is presented. This makes it impossible for me to use the rise and fall around a threshold and therefore decode audio morse. I've even tried the simple example that seems to be copied everywhere, but it also varies... I can't work out what I'm doing wrong, and my maths is not clever

问题 I was wondering how is it possible to detect new peaks within an FFT plot in Python. let's say i have this simple Plot: And i want to automatically measure the 'Similarity' or the Peaks location within a noisy Signal, i have tried to use the cosine Similarity but my real Signal is way too noisy, and with even if i add a new peak to the signal, i keep getting a Cosine of 0.9 since it's only one peak. This is an example of my real signal, and i also have the problem that my signal can be

问题 I was wondering how is it possible to detect new peaks within an FFT plot in Python. let's say i have this simple Plot: And i want to automatically measure the 'Similarity' or the Peaks location within a noisy Signal, i have tried to use the cosine Similarity but my real Signal is way too noisy, and with even if i add a new peak to the signal, i keep getting a Cosine of 0.9 since it's only one peak. This is an example of my real signal, and i also have the problem that my signal can be

问题 My question is the following: I have all the values that I need for a spectrogram ( scipy.fftpack.fft ). I would like to create a 3D spectrogram in python. In MATLAB this is a very simple task, while in python it seems much more complicated. I tried mayavi, 3D plotting matplotlib but I have not managed to do this. Thanks My code: import numpy as np import pandas as pd import numpy as np from scipy import signal import matplotlib.pyplot as plt from mpl_toolkits.mplot3d import Axes3D from

问题 How do I take a wav file, transform it into an array of frequency intensities every couple ms, do something with that array then transform that new array back into a wav file. Is there a library that looks something like this wav_data = library.read_wav('aoeu.wav') # [0, 3, 201, ... etc] spectrum = library.get_spectrum(wav_data) # [[0, 0, 0, .2, 0, .7, ... etc], # [0, 0, 0, .3, 0, .8, ... etc], # ... etc] spectrum[:, 0] = 0 # kill the lowest frequency (assuming spectrum is a numpy array)

问题 How do I take a wav file, transform it into an array of frequency intensities every couple ms, do something with that array then transform that new array back into a wav file. Is there a library that looks something like this wav_data = library.read_wav('aoeu.wav') # [0, 3, 201, ... etc] spectrum = library.get_spectrum(wav_data) # [[0, 0, 0, .2, 0, .7, ... etc], # [0, 0, 0, .3, 0, .8, ... etc], # ... etc] spectrum[:, 0] = 0 # kill the lowest frequency (assuming spectrum is a numpy array)

问题 How do I take a wav file, transform it into an array of frequency intensities every couple ms, do something with that array then transform that new array back into a wav file. Is there a library that looks something like this wav_data = library.read_wav('aoeu.wav') # [0, 3, 201, ... etc] spectrum = library.get_spectrum(wav_data) # [[0, 0, 0, .2, 0, .7, ... etc], # [0, 0, 0, .3, 0, .8, ... etc], # ... etc] spectrum[:, 0] = 0 # kill the lowest frequency (assuming spectrum is a numpy array)