Using Cantor Sets for Error Detection

Nagaraj, Nithin (2019) Using Cantor Sets for Error Detection. PeerJ Computer Science.

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Abstract: Error detection is a fundamental need in most computer networks and communication systems in order to combat the effect of noise. Error detection techniques have also been incorporated with lossless data compression algorithms for transmission across communication networks. In this paper, we propose to incorporate a novel error detection scheme into a Shannon optimal lossless data compression algorithm known as Generalized Luröth Series (GLS) coding. GLS-coding is a generalization of the popular Arithmetic Coding which is an integral part of the JPEG2000 standard for still image compression. GLS-coding encodes the input message as a symbolic sequence on an appropriate 1D chaotic map Generalized Luröth Series (GLS) and the compressed file is obtained as the initial value by iterating backwards on the map. However, in the presence of noise, even small errors in the compressed file leads to catastrophic decoding errors owing to sensitive dependence on initial values, the hallmark of deterministic chaos. In this paper, we first show that repetition codes, the oldest and the most basic error correction and detection codes in literature, actually lie on a Cantor set with a fractal dimension of 1n1n, which is also the rate of the code. Inspired by this, we incorporate error detection capability to GLS-coding by ensuring that the compressed file (initial value on the chaotic map) lies on a Cantor set. Even a 1-bit error in the initial value will throw it outside the Cantor set, which can be detected while decoding. The rate of the code can be adjusted by the fractal dimension of the Cantor set, thereby controlling the error detection performance.
Item Type: Article
Additional Information: Copyright belongs to the Publisher
Keywords: Error detection, Error control coding, Cantor sets, Shannon entropy, Arithmetic coding, Repetition codes, GLS-coding, Chaos, Lossless data compression
Subjects: School of Humanities > Consciousness Studies
Programmes > Consciousness Studies Programme
Divisions: Schools > Humanities
Date Deposited: 13 Mar 2019 11:48
Last Modified: 13 Mar 2019 11:48
Official URL: https://peerj.com/articles/cs-171/
Related URLs:
    Funders: UNSPECIFIED
    Projects: UNSPECIFIED
    URI: http://eprints.nias.res.in/id/eprint/1758

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