Binarized cross-approximate entropy in crowdsensing environment

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• 作者：Tamara Skoric^a ; ^{ceranic@uns.ac.rs} ; Omer Mohamoud^a ; ^{hafshook@gmail.com} ; Branislav Milovanovic^b ; ^c ; ^{branislav_milovanovic@vektor.net} ; Nina Japundzic-Zigon^b ; ^{nzigon@med.bg.ac.rs} ; Dragana Bajic^a ; ^{dragana.bajic@gmail.com} ; ^{draganab@uns.ac.rs}
• 关键词：Cross-approximate entropy ; Conditional entropy ; Differential coding ; Crowdsensing ; Cardiovascular signals
• 刊名：Computers in Biology and Medicine
• 出版年：2017
• 出版时间：1 January 2017
• 年：2017
• 卷：80
• 期：Complete
• 页码：137-147
• 全文大小：701 K
• 卷排序：80

文摘

A binarised cross-approximate entropy modification is proposed. It ensures speedy, computationally efficient and unsupervised implementation. Binary coding reduces sensitivity but minimizes adverse effects of instability. A special case of binarised entropy is equivalent to Shan n’s entropy. It embeds a dynamic observation of complexity changes at processing costs.