Offset removal from a sinusoidal wave
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Hello Everyone,
I have an input waveform as shown in the figure in blue. It is a sinusoidal wave but due to different offests during positive and negative half cycles, it looks distorted. Basically, there is a big jump whenever signal changes direction from positive to negative and vice versa. So, I want to remove offsets from individual half cycles. I want an output which looks as red in the figure, which is just shifting of top and bottom parts of the waveform, taking zero as the baseline, excluding the big jumps. I have attached the input csv file as well. If anyone has any idea, how to approach it, please let me know, I will be thankful.
采纳的回答
Star Strider
2021-2-18
Try this:
D1 = readmatrix('Output.csv');
x = 1:numel(D1);
D1HL = min(D1(D1>0));
D1HI = (D1>D1HL); % Logical Index
D1LL = max(D1(D1<0));
D1LI = (D1<D1LL); % Logical Index
minH = zeros(size(D1))+min(D1(D1HI));
maxL = zeros(size(D1))+max(D1(D1LI));
D1C = zeros(size(D1));
D1C(D1HI) = D1(D1HI)-minH(D1HI);
D1C(D1LI) = D1(D1LI)-maxL(D1LI);
figure
plot(x, D1C)
grid
xlim([0 100]) % Delete Or Change To See Larger (Or Entire) Vector
producing:
I plotted the points as well as the connecting lines to demonstrate the continuity. Change the line style to '-' to plot it without the points.
.
4 个评论
Mohammad Zulqarnain
2021-2-18
编辑：Mohammad Zulqarnain
2021-2-18
Star Strider
2021-2-18
Your data has outliers, so it is necessary to remove them first.
Try this:
D1 = readmatrix('OutputFull.csv');
x = 1:numel(D1);
D1HI = (D1>0); % Logical Index
D1H = D1(D1HI);
D1(D1HI) = filloutliers(D1H,'linear'); % Detect & Linearly Interpolate Outliers
D1HL = min(D1(D1HI))
D1LI = (D1<0); % Logical Index
D1L = D1(D1LI);
D1(D1LI) = filloutliers(D1L,'linear'); % Detect & Linearly Interpolate Outliers
D1LL = max(D1(D1LI));
minH = zeros(size(D1))+min(D1(D1HI));
maxL = zeros(size(D1))+max(D1(D1LI));
D1C = zeros(size(D1));
D1C(D1HI) = D1(D1HI)-minH(D1HI);
D1C(D1LI) = D1(D1LI)-maxL(D1LI);
figure
plot(x, D1C, '.-')
grid
xlim([0 100]) % Delete Or Change To See Larger (Or Entire) Vector
producing:
Other than removing the outliers (and sllight changes needed to reflect that), the code is essentially the same as previously. This code should be robust to other such data sets.
Mohammad Zulqarnain
2021-2-19
Star Strider
2021-2-19
As always, my pleasure!
更多回答（1 个）
darova
2021-2-18
I have an idea
clc,clear
x = linspace(0,20,100);
y = sin(x);
ind = -0.5<y & y<0.5;
x1 = x(~ind);
y1 = y(~ind);
y1 = y1 - sign(y1)*0.3;
plot(x,y)
hold on
plot(x1,y1,'.r')
hold off
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