先验不确定性条件下反滤波算法参数的优化

A.A. Polevoy, M. Simonov, V. E. Shuvalov
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引用次数: 1

摘要

考虑了一阶Volterra积分方程正则化算法精度的提高。这些问题描述了当所需解的功率谱的有效功率集中在有限频带(包括近周期解)时,动态目标识别和输入信号恢复的任务。在Tikhonov正则化方法的系统结构模拟中,提出使用特征参数数量最少的滤波器作为Butterworth滤波器的组合作为稳定器。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimization algorithm parameters of an inverse filtration in conditions of a priori indeterminacy
The accuracy increase of regularizing algorithms of the Volterra integral equations of 1-st order are considered. These problems describe tasks of dynamic objects identification and restoration of input signals for cases, when the effective power of a power spectrum of the required solution is concentrated in the limited frequencies band, including the almost periodic solutions. It is proposed to use filters with the minimal number of characteristic parameters, as a combination of Butterworth filters, as stabilizers in system-structural analogue of Tikhonov's regularization method.
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