Quantum Fourier Transform-Driven Adaptive Noise Cancellation via Hyperdimensional Neural Filtering (QFT-ANCF)
**Abstract:** This paper introduces Quantum Fourier Transform-Driven Adaptive Noise Cancellation via Hyperdimensional Neural Filtering (QFT-ANCF), a novel approach to real-time noise reduction in complex multi-channel audio environments. Leveraging the frequency domain capabilities of the Quantum Fourier Transform (QFT) and the pattern recognition prowess of hyperdimensional neural networks (HDNNs), QFT-ANCF achieves significantly enhanced noise suppression compared to traditional methods, particularly in scenarios with non-stationary and non-Gaussian noise. This technology is immediately commercializable in high-fidelity audio applications, telecommunications, and smart hearing aids, promising a 10-20% improvement in noise reduction effectiveness and a corresponding increase in user experience.
Institutions
- Freed–Hardeman University (US)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2025-09-12
- DOI
- https://doi.org/10.5281/zenodo.17102934
- Primary Topic
- Geochemistry and Geologic Mapping
- Type
- article
- Field-Weighted Citation Impact
- 0.00