首页> 外文期刊>Measurement techniques >DECOMPOSITION AND REGULARIZATION OF THE SOLUTION OF ILL-CONDITIONED INVERSE PROBLEMS IN PROCESSING OF MEASUREMENT INFORMATION. PART 1. A THEORETICAL EVALUTION OF THE METHOD
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DECOMPOSITION AND REGULARIZATION OF THE SOLUTION OF ILL-CONDITIONED INVERSE PROBLEMS IN PROCESSING OF MEASUREMENT INFORMATION. PART 1. A THEORETICAL EVALUTION OF THE METHOD

机译:测量信息处理中病态逆问题解的分解与调整。第1部分。方法的理论评价

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摘要

A theoretical evaluation of a method of solving ill-conditioned inverse problems that arise in mathematicostatistical processing of measurement information under conditions of unavoidable errors in measurements and a mathematical model of the study object is considered. The method is based on physical and canonical decomposition of the initial model of the object, specified in the form of a system of linear equations as well as two-sided regularization of the solution of a canonical (diagonal) system of equations. It is shown that through the use of the method it is possible to create an adaptive algorithm for recognition and stable estimation of a group of information parameters of a physically decomposed model.
机译:考虑了解决不可避免的测量误差条件下的测量信息的数学统计处理中出现的病态逆问题的方法的理论评估,并考虑了研究对象的数学模型。该方法基于对象初始模型的物理和规范分解,以线性方程组和规范(对角)方程组解的两侧正则化形式指定。结果表明,通过使用该方法,可以创建用于识别和稳定估计物理分解模型的一组信息参数的自适应算法。

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