MatlabFunctions

Repository of personal function developed in matlab

• Spike Removal function

  available for download also on Matlab File Exchange

  This function removes spikes that go over the threshold value mu each array element that is over mu is averaged between previous and subsequent element if spikes occur in the first or last element of the array, it filters it using the nearest value

  Example:

  clear
  clc
  
  x=0.1*sin(2*pi*0.5*[0:0.01:20])+0.2*sin(2*pi*1*[0:0.01:20]);
  r=randi([1 length(x)],20,1);
  mu=2*std(x);
  
  x(r)=0.5;
  x(1)=1.5;
  x(end)=2;
  
  plot(x)
  hold on
  plot(spikeRemoval(x,mu),'r')
  hold off
  grid on

  

• Iterative Gauss-Seidel linear system solver

  available for download also on Matlab File Exchange

  This function solves linear system with gauss seidel method. Consider the linear system model: A*x=b , the function sintax is: [x,execution_time]=itergauss(A,b,n) [x] is the solution vector A is the linear matrix of the problem b is the known term vector n is the number of iterative approximation execution_time is the time needed to solve the system

• Adaptive downsampling of arrays

  available for download also on Matlab File Exchange

  This function uses the derivative and the standard deviation to remove, less significant samples fron long arrays (those that do not add much information like constant segment, that can be reconstructed with a simple linear interpolation), reducing size and memory allocation.

  Example:

  clear all
  clc
  
  y=0.5*sin(0.5*pi*[0:0.01:10*pi])+0.5;
  y=[y,zeros(1,500),ones(1,500),zeros(1,500)];
  x=0:length(y)-1;
  
  [x_final,y_final] = adaptiveDownsampling(x,y,0.001);
  
  plot(x,y);
  hold on
  plot(x_final,y_final);
  grid on

  

  The start arrays has both 4642 element, the final ones only 2895. A compression rate of 37,65%

  Like all the compression algorithm the threshold value that set the "loss of precision" causes small error in some part of the signal where there is a small derivative.