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General Regression Neural Network Based Audio Watermarking Algorithm Using Torus Automorphism

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F18%3APU129591" target="_blank" >RIV/00216305:26220/18:PU129591 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1109/TSP.2018.8441174" target="_blank" >http://dx.doi.org/10.1109/TSP.2018.8441174</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1109/TSP.2018.8441174" target="_blank" >10.1109/TSP.2018.8441174</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    General Regression Neural Network Based Audio Watermarking Algorithm Using Torus Automorphism

  • Original language description

    Accurate extraction of embedded data at the receiver end is still a major point of consideration in audio watermarking area. This paper portrays a blind audio watermarking scheme in transform domain using the combination of properties of audio signal extracted through singular value decomposition and general regression neural network leading to exact extraction of watermark. The security of embedded watermark is assured by using torus automorphism at the embedded side. Results from the experimental setup validate the accuracy of proposed scheme. The payload capacity of proposed algorithm is 62.5 bps. The comparison of proposed scheme with existing ones indicate that the proposed scheme has shown good efficiency in terms of robustness, payload and transparency.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20203 - Telecommunications

Result continuities

  • Project

    <a href="/en/project/LO1401" target="_blank" >LO1401: Interdisciplinary Research of Wireless Technologies</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2018

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the IEEE 2018 41st International Conference on Telecommunications and Signal Processing (TSP2018)

  • ISBN

    978-1-5386-4695-3

  • ISSN

  • e-ISSN

  • Number of pages

    4

  • Pages from-to

    1-4

  • Publisher name

    IEEE

  • Place of publication

    Athens, Greece

  • Event location

    Athens, Greece

  • Event date

    Jul 4, 2018

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article

    000454845100084