The Control of Accuracy of Information Transmission in Systems of Unsteady Nature Data Processing

A. Abdullayev
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Abstract

The complex of methods, models, algorithms and software of accuracy increase of unsteady nature data control on the basis of use of statistical and dynamic data properties has been investigated and developed; the areas of their efficiency and limiting probabilities have been investigated; the algorithms of information control in operation of remote system data processing, as well as in the systems of images processing of micro objects have been practically realized. Calculation techniques of statistical parameters of the controlled information have been developed. The estimations of root-mean-square errors of information control for a wide class of data control algorithms on borders of the permitted values, on increments have been received. Principles and rules of the adaptive data control of unsteady process have been developed by regulation of control borders, regulation of borders arrangement level, change of parameters of statistical prediction models, the choice of optimum models on increments characteristics, the choice of the best models and algorithms of a neural network which allows to reduce information errors considerably at discovered errors correction. The general and individual decisions of problems giving estimations of efficiency area and limiting probabilities of developed algorithms have been received.
非定常数据处理系统中信息传递精度的控制
研究开发了利用统计和动态数据特性提高非定常数据控制精度的方法、模型、算法和软件;研究了它们的效率和极限概率的范围;实现了远程系统数据处理操作中的信息控制算法,以及微目标图像处理系统中的信息控制算法。被控信息统计参数的计算技术得到了发展。对于一类广泛的数据控制算法的信息控制的均方根误差估计在允许值的边界上,在增量上已经收到。本文从控制边界的调整、边界排列水平的调整、统计预测模型参数的改变、增量特性最优模型的选择、最优模型的选择和神经网络的算法等方面提出了非定常过程自适应数据控制的原理和规则。给出了所开发算法的效率区域和极限概率估计的问题的一般和个别决策。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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