Inherent Flexibility of Mathematical Splines for Pulse Shape Reconstruction

  • Aba A. Bentil Andam
Keywords: pulse shape, data fitting, minimization, analyticity, spline, knots

Abstract

Effective retrieval of information from digitised pulse shape data depends on a good data fitting procedure. Polynomial approximation, although easy to compute, results in curve oscillation and interpolation when high order polynomials are used. In addition, the analyticity of polynomials introduces a major drawback of global dependence on local properties in the interval of approximation. The use of mathematical splines helps to over-come these problems. A quartic spline of order 5 with 6 knots has been used to reconstruct digitised Cerenkov light pulse shapes. The pulse shape parameters measured are consistent with measurements from other experiments.

Published
2016-01-11
How to Cite
Andam, A. A. B. (2016). Inherent Flexibility of Mathematical Splines for Pulse Shape Reconstruction . Journal of Science and Technology, 10(3), 126- 133. https://doi.org/10.4314/just.v10i3.1070
Section
Articles