Short Time Fourier Transform (STFT)

To visualize the STFT of a signal for further processing

%% function [t,frequency,Power_spectrum]=fft_s(y,windowlength)
%% Inputs :
% y: input raw signal
% windowlength: window length to take fast fourier transform, it is a
% factor of smapling frequency for example one can enter a window length
% half of the sampling frequency by enteríng 0.5 and if fs =1000, then the
% window is 500 samples length
% reshaping: reshapes the signal to the length of the windowlength. if your
% signal is already chunked make it zeros otherwise it is should always be
% =1;
% gr : plot or not (0 plot, 1 no plot)

%% Example : [t,frequency,Power_spectrum]=fft_s(EMG,0.1,1000,1,1)
%% Outputs :
% t : time
% frequency : Frequency
% Power_spectrum : Power spectrum
%% Method:
% Chunks the signal with th elength of windowlength and gets the
% fast fourier transform and outputs a 3d plot
%% Tuning
% for a better resolution in time domain reduce the windowlength and for a
% better resolution in frequency domain increase the windowlength.
% Keep in mind that wavelet transform is in the most cases more effective and dont have
% the resolution problem in one domain

% Author : Hooman Sedghamiz ([e-mail])
% Graduate student Linköping University
%% Frequency analysis (FFT with plot)
% Fast Fourier Transform Windowed