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Upsampling01:22

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Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
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Accurate signal sampling and reconstruction are crucial in various signal-processing applications. A time-domain signal's spectrum can be revealed using its Fourier transform. When this signal is sampled at a specific frequency, it results in multiple scaled replicas of the original spectrum in the frequency domain. The spacing of these replicas is determined by the sampling frequency.
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The application of Fourier Transform properties in radio broadcasting is multifaceted, enabling significant advancements in the way signals are transmitted and received. Key areas where these properties are utilized include simultaneous multi-channel transmission, audio clip speed adjustments, live broadcast delays for different time zones, audio frequency adjustments, and signal demodulation.
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An efficient watermarking algorithm for digital audio data in security applications.

Mohamed Yamni1, Achraf Daoui2, Hicham Karmouni2

  • 1CED-ST, STIC, Laboratory of Electronic Signals and Systems of Information LESSI, Faculty of Science Dhar El Mahrez, University Sidi Mohamed Ben Abdellah, Fez, Morocco.

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This study introduces a faster audio watermarking system using parallel processing on Raspberry Pi clusters. The novel approach significantly improves speed for real-time applications, enhancing security in smart cities.

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Area of Science:

  • Digital Signal Processing
  • Embedded Systems
  • Information Security

Background:

  • Transform-domain audio watermarking offers robustness but suffers from high computational costs, limiting real-time applications.
  • Existing methods are often too slow for time-critical security needs, especially with long audio signals.

Purpose of the Study:

  • To develop a computationally efficient and fast audio watermarking system for real-time security applications.
  • To leverage parallel processing on embedded systems to overcome the speed limitations of transform-domain watermarking.

Main Methods:

  • A hybrid transform domain using fractional Charlier transform (FrCT) and dual-tree complex wavelet transform (DTCWT) was employed.
  • Intensive watermarking steps were parallelized and implemented on a cluster of four Raspberry Pi 4B devices using Message Passing Interface (MPI).

Main Results:

  • The parallelized system achieved significant temporal improvements: approximately 70% with 4 cores, 80% with 8 cores, and 90% with 16 cores.
  • The system demonstrated robustness against manipulation, high payload capacity, and high imperceptibility.

Conclusions:

  • The proposed parallel audio watermarking system effectively addresses the computational cost challenge.
  • The portable and low-power Raspberry Pi cluster enables efficient, real-time watermarking for smart city applications.