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Published:
Dec 14, 1990Keywords:
Pulse Shape Data Fitting Minimization Analyticity Spline Knots
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The copyright of a submitted article is only transferred to the publishers if and when the article is accepted for publication. All rights reserved. No part of this publication may be reproduced, stored in a retrieval system or transmitted in any form or by any means, electronic, electrostatic, mechanical, photocopying, recording or otherwise without the prior written permission of the publishers.
Main Article Content
Inherent Flexibility of Mathematical Splines for Pulse Shape Reconstruction
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.
