Your sum depends only on m so I assume that other parameters as well as function H((m+n)/(NT)) are defined. Via for-loops the simplest one is: function [S]=discrete_s_transform(x); N=length(x); % length of signal S=0; m=0; for i=1:N S=S+H((m+n)/(NT))*exp(a)*exp(b*m/N); m=m+1; end Hope that helps!...

The basic idea is that the DWT for the "true" (noise free) image is sparse, i.e. most of the "image energy" is concentrated in a few isolated DWT bins, while the DWT of noise is noise as well - it's distributed more or less evenly among the DWT bins. And...

matlab,signal-processing,wavelet,wavelet-transform,continuous-fourier

Because we are dealing with digitized signals. You can not plot an infinite amount of samples of your signal. That is why you need to specify some parameters prior to working with digitized signals, such as the sampling frequency. The sampling frequency gives you a relationship between your samples indices...

opencv,image-processing,image-segmentation,wavelet,wavelet-transform

Instead of attempting to use the traditional wavelet transform, you may want to try Haar-like wavelets tuned for object detection tasks, similar to the basis of integral images used in the Viola Jones face detector. This paper by Lienhart et al, used for generic object detection, would be a good...

Posting my comment as answer: I don't have much idea of the s-transform, but AFAIK the result of it is a 3D signal (as you can clearly see in the size of ST), so you may want to do imagesc(abs(ST)) or surf(abs(ST),'linestyle','none') instead of plot. In your figure you have...

signal-processing,fft,wavelet,haar-wavelet,wavelet-transform

note that, the width of the winow function is constant throughout the entire STFT process. and the time (t) in the function g(t-t') indicate sthat, t: is the current time on the time axis and it is variable each time the window is moved/shifted to the righ to overlap the...

matlab,image-processing,wavelet,dwt

I'm curious as to why you can't use dwt2 for computing the 2D DWT of images. What you have there is a lot more work than what you should be doing. dwt2 is much more suitable to do what you want. You'd call dwt2 like so: [LL,LH,HL,HH] = dwt2(X,Lo_D,Hi_D); X...

matlab,signal-processing,fft,wavelet,haar-wavelet

Idea: get the axis the was used to plot the spectrogram and set its properties accordingly. For example, supposing you'd want to restrict the x range to [0, 0.5] and y to [100, 200], then: %'old code here' %' . . . ' spectrogram(x4,128,50,NFFT); %'new code here' axis(get(gcf,'children'), [0, 0.5,...

The error is pretty clear. Your image must have dimensions that belong to a power of two. As such, you need to resize your image so that it follows this. qtdecomp computes the quadtree decomposition algorithm, and a pre-condition for this function is that it NEEDS to have an image...

matlab,signal-processing,fft,wavelet

You can not see what you expected because the value of NFFT is 1 means when you write NFFT/2+1 as an index of Y it will not be an integer value so MATLAB warns you. You can calculate NFFT like this: NFFT = 2^nextpow2(length(t)) instead of writing NFFT = 2^nextpow2(StopTime)...

signal-processing,wavelet,haar-wavelet,wavelet-transform

the raw signal what ever it is measuring it is a function of time "time-domain" which means if we plotted the "time-domain" we will get one axes for the time (t), which is independent, and another axes for the Amplitude (x(t)) which is dependent variable on the time. Note that:...

python,python-3.x,wavelet,kubuntu,pywt

On Kubuntu 14.04 using Python 3.4, I installed the packages (for Python 3): python3-all-dev, and the respective ones related to numpy and Cython. Then I clonned the sorce from the github repo pywt repo. After that I was able to do: $ python setup.py install --user The build and install...

matlab,signal-processing,fft,wavelet

Replace the last four lines by hold on %// this prevents each subsequent `plot` from removing the previous graph plot(t1,x1,'r'); %// use appropriate "t" vector: `t1` in this case plot(t2,x2,'g'); plot(t3,x3,'b'); plot(t4,x4,'black'); ...