Matlab codes for calculation of rank order statistic (ros) by adaptive coarse grain

calculate rank order statistic (ros) by adaptive coarse grain

function [ros,word_index]=ros_acg(x,m)
% calculate rank order statistic (ros) by adaptive coarse grain
% --------------------------
% CALL:
% [ros,word_index]=ros_acg(x,m)
% --------------------------
% INPUT:
% x - original time series
% m - word size (default 8)
% --------------------------
% OUTPUT:
% ros - rank order statistic
% word_index - word index
% --------------------------
% Matlab codes for calculation of rank order statistic (ros) by adaptive coarse grain
% --------------------------
% Reference:
% Jinshan Lin, Chunhong Dou. A novel method for condition monitoring
% of rotating machinery based on statistical linguistic analysis and weighted
% similarity measures. Journal of Sound and Vibration, 2017, 390: 272-288.
% --------------------------
% Author: Jinshan Lin
% E-mail:[e-mail]
% --------------------------
% Example:
% clear;
% x=randn(1,10000);
% [ros,word_index]=ros_acg(x,10);
% --------------------------
% Default parameters
if (nargin<1)
error('Not enough Input arguments');
end
if (nargin<2)
m = 8;
end

data_length=length(x);

% Convert original series into binary symbolic series
binary_series=zeros(data_length-1,1);
for i=1:data_length-1
if x(i)<x(i+1)
binary_series(i)=1;
else
binary_series(i)=0;
end
end

% Convert binary symbolic series into binary "word" according to the preset word size of m
m_bit_matrix_row_number=data_length-m;
m_bit_matrix=zeros(m_bit_matrix_row_number,m);
for j=1:m_bit_matrix_row_number
m_bit_matrix(j,:)=binary_series(j:j+m-1);
end

% Convert binary words into decimal words
m_bit_matrix_decimal=zeros(m_bit_matrix_row_number,1);
a=zeros(m,1);
for j=1:m_bit_matrix_row_number
for p=1:m
a(p)=m_bit_matrix(j,p)*2^(m-p);
m_bit_matrix_decimal(j)=a(p)+m_bit_matrix_decimal(j);
end
end

% Calculat frequency of each word
word_index=zeros(2^m,1);
for q=1:2^m
word_index(q)=length(find(m_bit_matrix_decimal==(q-1)));
end

% Calculate the descending statistic "ros" of words
ros=sort(word_index,'descend');
ros=ros/m_bit_matrix_row_number;

figure(1)
plot(word_index,'k');xlabel('Word Index');ylabel('Word Frequency');
hold on;

figure(2)
loglog(ros,'k');xlabel('Rank Index');ylabel('Probability');
hold on;