MIN_MAX_NORM_CVIP
min_max_norm_cvip() -applies min-max normalization to set of feature vectors in a matrix.
Contents
SYNTAX
a = min_max_norm_cvip(vector, s_min, s_max)
Input parameters include :
- vector - An m by n numerical matrix where m is the number of vectors and n is the length of each row vector.
- s_min - The min parameter in Min-Max normalization.
- s_max - The max parameter in Min-Max normalization.
Output Parameter includes :
- a - A matrix with the same size as the input 'vector' , where each column(feature vector) is normalized using Min-Max.
DESCRIPTION
This function assumes each row of the matrix vector corresponds to the features of an object. It then normalizes each column using the min-max normalization method.
REFERENCE
1. Scott E Umbaugh. DIGITAL IMAGE PROCESSING AND ANALYSIS: Applications with MATLAB and CVIPtools, 3rd Edition.
EXAMPLE
% Input vector vectors = randn(13,6); % minimun parameter s_min = 0; % maximum parameter s_max = 1; % calling function a = min_max_norm_cvip(vectors, 0, 1)
a =
0.4171 0.4529 0.3286 0.6077 0.1064 0
0.7382 0.9429 0.5904 0.4777 0.4367 0.0508
0.7048 0.1654 0.5235 1.0000 1.0000 0.7561
0.2574 0.0318 0 0.2665 0.5740 1.0000
0 0.2659 0.4800 0 0.9420 0.6271
0.6822 0.5087 0.6478 0.2361 0.6802 0.5926
0.3002 0.2032 0.5899 0.5772 0 0.4476
0.7438 1.0000 1.0000 0.7908 0.6015 0.8639
0.5784 0 0.6623 0.1335 0.6786 0.8809
1.0000 0.6610 0.5356 0.3567 0.3982 0.3817
0.3772 0.6664 0.0511 0.6758 0.9196 0.4176
0.8259 0.4876 0.5362 0.4892 0.3012 0.6032
0.7451 0.9433 0.6975 0.4852 0.5542 0.1639
CREDITS
Author: Mehrdad Alvandipour, March 2017
Copyright © 2017-2018 Scott
E Umbaugh
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