wavelet

问题 I need to denoise a signal. I tried to denoise it with savgol_filter but it result in loosing singularities in the signal. In order to denoise and keep singularities i tried to use wavelet transform, wavelet thresholding and inverse wavelet transform but i didn't succeed. Does someone know how to use wavelet denoising ? here is a text file with signal datas import numpy as np from matplotlib import pyplot as plt from scipy.signal import savgol_filter import pywt def readSignal(nomFichier, N):

问题 In cwt() I can specify which wavelet function to use. How does that impact the speed of cwt() ? 回答1: Here is a benchmark, which I run with the -singleCompThread option when starting MATLAB to force it to use a single computational thread. cwt() was passed a 1,000,000-sample signal and asked to compute scales 1 to 10. My CPU is an i7-3610QM. Code used: clear all %% Benchmark parameters results_file_name = 'results_scale1-10.csv'; number_of_random_runs = 10; scales = 1:10; number_of_random

问题 I am trying to use the functions provided in the Matlab Wavelet Toolbox to create a multi-level discrete wavelet decomposition of an image, extracting the coefficients, manipulating them, and recomposing them back into the image. I tried using a number of functions but none of them seem to do what I need. These are the steps to do this. Use wavedec2 to decompose the image into [C,S]. [C,S] = wavedec2(X,N,Lo_D,Hi_D) I then must use detcoef2 to extract the detail coefficients from [C,S]. [C,S]

问题 I am discovering wavelets in practice thanks to the python module pywt. I have browsed some examples of the pywt module usage, but I could not grasp the essential step: I don't know how to display the multidimensionnal output of a wavelet analysis with matplotlib , basically. This is what I tried, (given one pyplot axe ax ): import pywt data_1_dimension_series = [0,0.1,0.2,0.4,-0.1,-0.1,-0.3,-0.4,1.0,1.0,1.0,0] # indeed my data_1_dimension_series is much longer cA, cD = pywt.dwt(data_1

问题 I have a vector of data, which contains integers in the range -20 20. Bellow is a plot with the values: This is a sample of 96 elements from the vector data. The majority of the elements are situated in the interval -2, 2, as can be seen from the above plot. I want to eliminate the noise from the data. I want to eliminate the low amplitude peaks, and keep the high amplitude peak, namely, peaks like the one at index 74. Basically, I just want to increase the contrast between the high amplitude

问题 As in the title, I am confused about the range of the coefficients of Wavelet LeGall 5/3 (has to be exact this filter) 2D transform (only for a 8*8 block) if the value of the input matrix are within the range from 0-255. For the formulas, the link is here: Wavelet LeGall 5/3 Here is what I did for now: Minus 128 for all value (easier to calculate the low frequency values, see later); Do the transform in horizontal direction. This will generate all coefficients in all lines: the first 4 are

问题 I have generated the non-stationary signals posted below in the image, and i have two questions: 1- Why the first signal x1 , shown in red, has only 4 peaks despite its frequency which is 15 in the equation at line-12 of code? 2- Why there is discontinuity between the signals shown? In other words, i expected the four signals to be linked smoothly and each signla starts where the previous one ends, but, that did not happens, and instead for an example, x1 ended at .25 and the x2 started at

问题 I'm trying to make a model for non parametric regression with Maximal Overlap Discrete Wavelet Transform (MODWT) using this data taken from here and here. The packages I'm using here are shiny , wavelets , and readxl . Here is my server code: server <- function(input, output) { dataset<-reactive({ inFile <- input$filewav dat <- read_excel(inFile$datapath) df <- data.frame(dat[,2], dat[,3]) x <- seq(1,nrow(df),length = nrow(df)) y <- df[,2] return(dat) }) output$plot_mra <- renderPlot({ filt <

问题 I want to ask some questions related to the last question of mine so I don't want to post in another thread. My question contains a code, I therefore can't post it as a comment. So I have to edit my old question into a new one. Please take a look and help. Thank you. I'm new to FFT and DSP and I want to ask you some questions about calculating FFT in Matlab. The following code is from Matlab help, I just removed the noise. Can I choose the length of signal L different from NFFT? I'm not sure

问题 I applied Gabor filter on images with the following theta - {0,45,90,135}. but the resultant images were exactly the same with the same orientation angle! I expected that the results of applying Gabor filter with theta = 90 will be different in orientation than the one with theat = 45 , but after using Gabor filter with different theta , I get images with no difference in orientation! Am I using Gabor filter wrong? Because I expect every image to be of different orientation according to the