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The Possibility for Full Profile Incoherent Scatter Data Processing on the Base of the Simplex-processor Algorithm

机译:SimpleX处理器算法基础上完整的全款散移数据处理的可能性

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For the processing of Irkutsk Incoherent Scatter Radar data we consider the problem of non-linear discrepancy functional minimization in long experimental data series processing when measured process is described by integro-differential equation. Considering the non-linear inverse problem for functions with two continuous derivatives determined on compact we present three main techniques parts: descent algorithm, genetic algorithm and solution regularization. The central part of the technique is the descent algorithm that works on n-dimensional net associated with some regular polytope. The regularization of solution is carried out by means of transition to Sobolev space. For deleting of ambiguities due to set of sub-optimal solution we use adaptation scheme on the base of genetic algorithms.
机译:为了处理Irkutsk非连贯散射雷达数据,我们考虑当通过积分微分方程描述测量过程时,在长实验数据序列处理中考虑非线性差异功能最小化的问题。考虑到具有在Compact上确定的两个连续衍生物的功能的非线性逆问题,我们呈现了三种主要技术部分:下降算法,遗传算法和解决方案正则化。该技术的中心部分是与某些常规Polytope相关联的N维网上工作的下降算法。解决方案的正则化通过过渡到SoboLev空间进行。为了删除因子最优解决方案集而删除歧义,我们在遗传算法基础上使用适应方案。

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