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Исследование алгоритмов сжатия измерительной информации с контролем возникающей погрешности

выпускная квалификационная работа магистра

Исследование алгоритмов сжатия измерительной информации с контролем возникающей погрешности

Abstract

Тема выпускной квалификационной работы: «Исследование алгоритмов сжатия измерительной информации с контролем возникающей погрешности». Данная работа посвящена исследованию существующих алгоритмов сжатия, возможности их применения к измерительным данным с контролем возникающей погрешности. Задачи, которые решались в ходе исследования: 1. Изучение существующих методов сжатия и предварительной обработки измерительных данных. 2. Рассмотрение способов сжатия данных с контролем погрешности. 3. Разработка программ, позволяющих производить сжатие измерительных данных с гарантированной точностью. В работе применяется предобработка измерительных данных для улучшения коэффициента сжатия. В первой части работы в качестве предобработки используется приведение измерительных данных к монохромному изображению и дальнейшее сжатие с потерями. Во второй части в исходные данные вносится погрешность в рамках заданной, после чего происходит сжатие без потерь. Для описанных подходов реализованы программы, позволяющие пользователю контролировать погрешность выходных данных. В результате работы выявлены зависимости коэффициента сжатия от следующих параметров: размер исходного набора данных, качество изображения, формат изображения, задаваемая допустимая погрешность.

The subject of the graduate qualification work is “Research of compression algorithms for measuring information with the control of the error”. The given work is devoted to studying defects of existing compression algorithms, the possibility of their application to the measurement data with the control of the arising error. The research set the following goals: 1. Research of existing methods of compression and pre-processing of measurement data. 2. Consideration of data compression methods with error control. 3. Development of programs that allow the compression of measurement data with guaranteed accuracy. In given work, preprocessing of measurement data is used to improve the compression ratio. In the first part of the work, preprocessing of the measurement data is used to convert them to a monochrome image that used further in lossy compression. In the second part, an error is introduced into the initial data within the specified range, then lossless compression applies to new data. For the described approaches, programs are implemented that allow the user to control the error of the output data. As a result of the work, the dependences of the compression coefficient on the following parameters were revealed: the size of the initial data set, image quality, image format, and the allowable error.

Keywords

gzip, measurement data, коэффициент сжатия, compression coefficient, Lempel-Ziv algorithm, error control, compression algorithm, алгоритм сжатия, Barrows-Wheeler transform, jpeg, Huffman coding, контроль погрешности, метод Хаффмана, семейство алгоритмов LZ, преобразование Барроуза-Уилера, измерительные данные

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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