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Giant FFTs for Sample-Rate Conversion

Vesa Välimäki, Stefan Bilbao

2023Journal of the Audio Engineering Society10 citationsDOIOpen Access PDF

Abstract

Funding Information: The main part of this work was conducted during a research visit of the second author to the Aalto Acoustics Lab between May 30 and June 13, 2022. This research belongs to the activities of the Nordic Sound and Music Computing Network—NordicSMC (NordForsk project no. 86892). For the purpose of open access, the second author has applied a creative commons attribution (CC BY) license to any author-accepted manuscript version arising. The authors would like to thank the Associate Technical Editor for noticing the surprising mismatch between the numerical precisions of the FFT spectrum and the time-domain signal reconstructed using the IFFT. Special thanks go to the anonymous reviewer who suggested testing the method by converting a signal to another sample rate and back. Publisher Copyright: © 2023 Authors. All rights reserved.

Topics & Concepts

RingingFast Fourier transformSample (material)Nyquist rateComputer scienceSampling (signal processing)Frequency domainNyquist–Shannon sampling theoremAlgorithmLimit (mathematics)SIGNAL (programming language)Nyquist frequencySpeech recognitionMathematicsTelecommunicationsBandwidth (computing)Filter (signal processing)Computer visionPhysicsThermodynamicsMathematical analysisProgramming languageImage and Signal Denoising MethodsAdvanced Electrical Measurement TechniquesAdvanced Image Processing Techniques
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