DECONVOLUTION OF INFREQUENTLY SAMPLED-DATA FOR THE ESTIMATION OF GROWTH-HORMONE SECRETION

被引：12

作者：

DENICOLAO, G

LIBERATI, D

SARTORIO, A

机构：

[1] POLITECN MILAN,CNR,CTR TEORIA SISTEMI,I-20133 MILAN,ITALY

[2] UNIV MILAN,OSPED MAGGIORE,IRCCS,IST SCI ENDOCRINE,I-20122 MILAN,ITALY

来源：

IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING | 1995年 / 42卷 / 07期

关键词：

D O I：

10.1109/10.391166

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

In this paper, the deconvolution of infrequently and nonuniformly sampled data is addressed. A nonparametric technique is worked out that provides a smooth estimate of the unknown input signal and takes into account nonnegativity constraints, In spite of the size of the problem, efficient algorithms for solving the constrained optimization problem and computing confidence intervals are proposed, The new technique is used to estimate growth hormone (GH) secretion after repeated GH-releasing hormone (GHRH) administration from samples of blood concentration.

引用

页码：678 / 687

页数：10

共 25 条

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ARVAT E, 1992, CLIN ENDOCRINOL OXF, V3, P347

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