TY - GEN
T1 - ZeChipC
T2 - 19th Mexican International Conference on Artificial Intelligence, MICAI 2020
AU - Miralles-Pechuán, Luis
AU - Bellucci, Matthieu
AU - Qureshi, M. Atif
AU - Namee, Brian Mac
N1 - Publisher Copyright:
© 2020, Springer Nature Switzerland AG.
PY - 2020
Y1 - 2020
N2 - In this paper, we present an interpolation method based on Lebesgue sampling that could help to develop systems based time series more efficiently. Our methods can transmit times series, frequently used in health monitoring, with the same level of accuracy but using much fewer data. Our method is based in Lebesgue sampling, which collects information depending on the values of the signal (e.g. the signal output is sampled when it crosses specific limits). Lebesgue sampling contains additional information about the shape of the signal in-between two sampled points. Using this information would allow generating an interpolated signal closer to the original one. In our contribution, we propose a novel time-series interpolation method designed explicitly for Lebesgue sampling called ZeChipC. ZeChipC is a combination of Zero-order hold and Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) interpolation. ZeChipC includes new functionality to adapt the reconstructed signal to concave/convex regions. The proposed methods have been compared with state-of-the-art interpolation methods using Lebesgue sampling and have offered higher average performance.
AB - In this paper, we present an interpolation method based on Lebesgue sampling that could help to develop systems based time series more efficiently. Our methods can transmit times series, frequently used in health monitoring, with the same level of accuracy but using much fewer data. Our method is based in Lebesgue sampling, which collects information depending on the values of the signal (e.g. the signal output is sampled when it crosses specific limits). Lebesgue sampling contains additional information about the shape of the signal in-between two sampled points. Using this information would allow generating an interpolated signal closer to the original one. In our contribution, we propose a novel time-series interpolation method designed explicitly for Lebesgue sampling called ZeChipC. ZeChipC is a combination of Zero-order hold and Piecewise Cubic Hermite Interpolating Polynomial (PCHIP) interpolation. ZeChipC includes new functionality to adapt the reconstructed signal to concave/convex regions. The proposed methods have been compared with state-of-the-art interpolation methods using Lebesgue sampling and have offered higher average performance.
KW - Event-based interpolation
KW - Lebesgue sampling interpolation method
KW - Signal reconstruction using Lebesgue sampling
KW - Time series interpolation method
UR - http://www.scopus.com/inward/record.url?scp=85092634363&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-60884-2_14
DO - 10.1007/978-3-030-60884-2_14
M3 - Conference contribution
AN - SCOPUS:85092634363
SN - 9783030608835
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 182
EP - 196
BT - Advances in Soft Computing - 19th Mexican International Conference on Artificial Intelligence, MICAI 2020, Proceedings
A2 - Martínez-Villaseñor, Lourdes
A2 - Ponce, Hiram
A2 - Herrera-Alcántara, Oscar
A2 - Castro-Espinoza, Félix A.
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 12 October 2020 through 17 October 2020
ER -