similaritymeasure#

[d] = similaritymeasure(x, y, CalcMethod, dispout)

Description#

Measure similarity between two arrays

Inputs#

x: First array, its similarity is measured against y array
y: Second array, its similarity is measured against x array
CalcMethod=’euclidean’: Similarity calculation method

‘euclidean’: Euclidean distance

‘manhattan’: Manhattan distance

‘minkowski’: Minkowski distance (power=3)

‘cosine’: Cosine distance

‘pearson’: Pearson’s correlation coefficient

‘spearman’: spearman’s correlation coefficient

‘norm’: Absolute difference of norm

‘covariance’: Covariance

‘inv_covariance’: Euclidean distance of inverse covariance

‘histogram’: Mean of absolute difference of histogram

‘t-test’: Two-sample t-test statistic
dispout=’no’: Define to display outputs or not (‘yes’: display, ‘no’: not display)

Outputs#

d: Arrays similarity measure

Examples#

x=[0,2,4,6];
y=[2,3,5,7];
[d]=similaritymeasure(x,y,'euclidean','yes');

x=[1,2,3,4,5,6,7,8,9,10];
y=[1.1,1.98,3.3,4.2,4.8,5.95,7.5,7.7,8.99,10.5];
[d]=similaritymeasure(x,y,'pearson','yes');

References#

Kianimajd, A., Ruano, M. G., Carvalho, P., Henriques, J., Rocha, T., Paredes, S., & Ruano, A. E. (2017). Comparison of different methods of measuring similarity in physiologic time series. IFAC-PapersOnLine, 50(1), 11005-11010.

similaritymeasure

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