How to remove noise from a plot?

To remove noise from a plot, you can use various filtering techniques. Here are a few common methods you can use in MATLAB:

1. **Moving Average Filter**: This smooths the data by averaging a subset of data points.
2. **Low-pass Filter**: This removes high-frequency noise by applying a low-pass filter.
3. **Savitzky-Golay Filter**: This smooths the data while preserving the shape of the signal.

### Example: Removing Noise Using a Moving Average Filter
```matlab
% Sample data with noise
t = 0:0.01:1;
y = sin(2*pi*5*t) + 0.5*randn(size(t)); % Signal with noise

% Moving average filter
windowSize = 5; 
y_smooth = filter(ones(1, windowSize)/windowSize, 1, y);

% Plot original and smoothed data
figure;
plot(t, y, 'r', t, y_smooth, 'b');
legend('Noisy Signal', 'Smoothed Signal');
title('Noise Removal Using Moving Average Filter');
xlabel('Time');
ylabel('Amplitude');
```

### Example: Removing Noise Using a Low-pass Filter
```matlab
% Sample data with noise
t = 0:0.01:1;
y = sin(2*pi*5*t) + 0.5*randn(size(t)); % Signal with noise

% Design a low-pass filter
fs = 100; % Sampling frequency
fc = 10; % Cut-off frequency
[b, a] = butter(6, fc/(fs/2)); % 6th order Butterworth filter

% Apply low-pass filter
y_filtered = filtfilt(b, a, y);

% Plot original and filtered data
figure;
plot(t, y, 'r', t, y_filtered, 'b');
legend('Noisy Signal', 'Filtered Signal');
title('Noise Removal Using Low-pass Filter');
xlabel('Time');
ylabel('Amplitude');
```

### Example: Removing Noise Using Savitzky-Golay Filter
```matlab
% Sample data with noise
t = 0:0.01:1;
y = sin(2*pi*5*t) + 0.5*randn(size(t)); % Signal with noise

% Apply Savitzky-Golay filter
windowSize = 11; % Odd number
polynomialOrder = 3;
y_smooth = sgolayfilt(y, polynomialOrder, windowSize);

% Plot original and smoothed data
figure;
plot(t, y, 'r', t, y_smooth, 'b');
legend('Noisy Signal', 'Smoothed Signal');
title('Noise Removal Using Savitzky-Golay Filter');
xlabel('Time');
ylabel('Amplitude');
```

Choose the method that best suits your data and the type of noise you are dealing with. Let me know if you need further help!