4 added 365 characters in body
source | link

For impulsive noises, you are probably better off with a Median filter than with a Gaussian Filter, since it is better able to remove the effect of outliers.

data = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["http://i.stack.imgur.com/RZcpj.png"],"Byte"]]]];
smoothed = MedianFilter[data, 5];
Show[ListPlot[data], ListPlot[smoothed, PlotStyle -> Green]]

enter image description here

And here is the same filtering applied to your second data set:

data2 = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["http://i.stack.imgur.com/WYcxd.png"], "Byte"]]]]; 
Show[ListPlot[data2], ListPlot[MedianFilter[data2, 5], PlotStyle -> Green]]

enter image description here

For impulsive noises, you are probably better off with a Median filter than with a Gaussian Filter, since it is better able to remove the effect of outliers.

data = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["http://i.stack.imgur.com/RZcpj.png"],"Byte"]]]];
smoothed = MedianFilter[data, 5];
Show[ListPlot[data], ListPlot[smoothed, PlotStyle -> Green]]

enter image description here

For impulsive noises, you are probably better off with a Median filter than with a Gaussian Filter, since it is better able to remove the effect of outliers.

data = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["http://i.stack.imgur.com/RZcpj.png"],"Byte"]]]];
smoothed = MedianFilter[data, 5];
Show[ListPlot[data], ListPlot[smoothed, PlotStyle -> Green]]

enter image description here

And here is the same filtering applied to your second data set:

data2 = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["http://i.stack.imgur.com/WYcxd.png"], "Byte"]]]]; 
Show[ListPlot[data2], ListPlot[MedianFilter[data2, 5], PlotStyle -> Green]]

enter image description here

3 added 65 characters in body
source | link

For impulsive noises, you are probably better off with a Median filter than with a Gaussian Filter, since it is better able to remove the effect of outliers.

data = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["http://i.stack.imgur.com/RZcpj.png"],"Byte"]]]];
smoothed = MedianFilter[data, 5];
Show[ListPlot[data], ListPlot[smoothed, PlotStyle -> Green]]

enter image description here

For impulsive noises, you are probably better off with a Median filter than with a Gaussian.

data = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["http://i.stack.imgur.com/RZcpj.png"],"Byte"]]]];
smoothed = MedianFilter[data, 5];
Show[ListPlot[data], ListPlot[smoothed, PlotStyle -> Green]]

enter image description here

For impulsive noises, you are probably better off with a Median filter than with a Gaussian Filter, since it is better able to remove the effect of outliers.

data = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["http://i.stack.imgur.com/RZcpj.png"],"Byte"]]]];
smoothed = MedianFilter[data, 5];
Show[ListPlot[data], ListPlot[smoothed, PlotStyle -> Green]]

enter image description here

2 added 125 characters in body
source | link

For impulsive noises, you are probably better off with a Median filter than with a Gaussian.

data = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["http://i.stack.imgur.com/RZcpj.png"],"Byte"]]]];
smoothed = MedianFilter[data, 5];
Show[ListPlot[data], ListPlot[smoothed, PlotStyle -> Green]]

enter image description here

For impulsive noises, you are probably better off with a Median filter than with a Gaussian.

smoothed = MedianFilter[data, 5];
Show[ListPlot[data], ListPlot[smoothed, PlotStyle -> Green]]

enter image description here

For impulsive noises, you are probably better off with a Median filter than with a Gaussian.

data = Uncompress[FromCharacterCode[
   Flatten[ImageData[Import["http://i.stack.imgur.com/RZcpj.png"],"Byte"]]]];
smoothed = MedianFilter[data, 5];
Show[ListPlot[data], ListPlot[smoothed, PlotStyle -> Green]]

enter image description here

1
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