Characterization of Functions Using Artificial Intelligence to Reproduce Complex Systems Behavior Takagi Sugeno Kang Order 2 to Reproduce Cardiac PQRST Complex

被引：0

作者：

Rodriguez-Flores, Jesus ^{[1
]}

Herrera-Perez, Victor ^{[1
]}

机构：

[1] Escuela Super Politecn Chimborazo, Fac Informat & Elect, Riobamba, Ecuador

来源：

APPLIED TECHNOLOGIES (ICAT 2019), PT II | 2020年 / 1194卷

关键词：

Characterization of functions; Fuzzy system; Cost function; Cardiac PQRST complex; Neuro-adaptive system; Lagrange interpolator; IDENTIFICATION;

D O I：

10.1007/978-3-030-42520-3_18

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

In the field of signal processing, for forecasting purposes, the characterization of functions is a key factor to be faced. In most of the cases, the characterization can be achieved by applying least square estimation (LSE) to polynomial functions; however, it is not fully in all cases. To contribute in this field, this article proposes a variant of artificial intelligence based on fuzzy characterization patterns initialized by Lagrange interpolators and trained with neuro-adaptive system. The aim is to minimize a cost function based on the absolute value between samples and their prediction. The proposal is applied to the characterization of cardiac PQRST complex as case study. The results show a satisfactory performance providing an error of around 1.42% compared to the normalized PQRST complex signal.

引用

页码：222 / 234

页数：13