basic global thresholding
The input is a vector x, the output is an estimated threshold T, which groups x into two clusters using the basic global thresholding
procedures:
1)Randomly select an initial estimate threshold T.
2)Segment the signal using T, which will yield two groups, G1 consisting of all points with values<=T and G2 consisting of points with value>T.
3)Compute the average distance between points of G1 and T, and points of G2 and T.
4)Compute a new threshold value T=(M1+M2)/2
5)Repeat steps 2 through 4 until the change of T is smaller enough.
Cite As
Rongwen Lu (2024). basic global thresholding (https://www.mathworks.com/matlabcentral/fileexchange/38390-basic-global-thresholding), MATLAB Central File Exchange. Retrieved .
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- Control Systems > System Identification Toolbox > Nonlinear Model Identification > Hammerstein-Wiener Models >
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1.0.0.0 |