Signal approximation with Pascal's triangle and sampling

被引：0

作者：

Chen, Lei ^{[1
]}

Yu, Xinghuo ^{[2
]}

Lu, Jinhu ^{[1
]}

机构：

[1] Beihang Univ, Beijing Adv Innovat Ctr Big Data & Brain Comp, Sch Automat Sci & Elect Engn, State Key Lab Software Dev Environm, Beijing 100191, Peoples R China

[2] RMIT Univ, Sch Engn, Melbourne, Vic 3001, Australia

来源：

PROCEEDINGS OF THE 32ND 2020 CHINESE CONTROL AND DECISION CONFERENCE (CCDC 2020) | 2020年

基金：

中国国家自然科学基金; 澳大利亚研究理事会;

关键词：

Signal approximation; Sampling; Discretization; CIRCUITS; ERROR;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

This brief explores the approximation properties of a unique basis expansion based on Pascal's triangle, which realizes a sampled-data driven approach between a continuous-time signal and its discrete-time representation. The roles of certain parameters, such as sampling time interval or model order, and signal characteristics, i.e., its curvature, on the approximation are investigated. Approximate errors in one and multiple-step predictions are analyzed. Furthermore, time-variant approximations under the thresholds of signal curvature are employed to narrow errors and provide flexibilities.

引用

页码：1571 / 1575

页数：5

共 19 条

[11] Approximating piecewise-smooth functions [J].