TY - GEN
T1 - Characterization of Functions Using Artificial Intelligence to Reproduce Complex Systems Behavior
T2 - 1st International Conference on Applied Technologies, ICAT 2019
AU - Rodríguez-Flores, Jesús
AU - Herrera-Pérez, Víctor
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - 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.
AB - 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.
KW - Cardiac PQRST complex
KW - Characterization of functions
KW - Cost function
KW - Fuzzy system
KW - Lagrange interpolator
KW - Neuro-adaptive system
UR - http://www.scopus.com/inward/record.url?scp=85082394404&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-42520-3_18
DO - 10.1007/978-3-030-42520-3_18
M3 - Contribución a la conferencia
AN - SCOPUS:85082394404
SN - 9783030425197
T3 - Communications in Computer and Information Science
SP - 222
EP - 234
BT - Applied Technologies - 1st International Conference, ICAT 2019, Proceedings
A2 - Botto-Tobar, Miguel
A2 - Zambrano Vizuete, Marcelo
A2 - Torres-Carrión, Pablo
A2 - Montes León, Sergio
A2 - Pizarro Vásquez, Guillermo
A2 - Durakovic, Benjamin
PB - Springer
Y2 - 3 December 2019 through 5 December 2019
ER -