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2019 | OriginalPaper | Chapter

Signal Distortion Identification Using Rough Flow Graphs

Authors : B. Jankar, B. Rajkumarsingh

Published in: Smart and Sustainable Engineering for Next Generation Applications

Publisher: Springer International Publishing

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Abstract

Rough Set Theory has been widely explored in the past decades and many hybrids have been developed as well. In this paper, rough set theory and temporal flow graphs have been used to detect distortions in sinusoidal signals. An episode information system is created in which data are stored in the form of integers, more specifically, 1, −1 and 0. The main objective of this work is to detect different kinds of disturbances that can occur in a specific range of sinusoidal signals. The design of the algorithm for the software was programmed in Java language. Several types of distortions have been tested and the results obtained from the temporal flow graphs show that the different distortions could be identified successfully.

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previous chapter Optimizing the Performance of Triple-Binary Turbo Codes with Hierarchical QAM and K-NN Based Classification
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Metadata
Title
Signal Distortion Identification Using Rough Flow Graphs
Authors
B. Jankar
B. Rajkumarsingh
Copyright Year
2019
Book
Smart and Sustainable Engineering for Next Generation Applications

Print ISBN: 978-3-030-18239-7

Electronic ISBN: 978-3-030-18240-3

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-3-030-18240-3_16