Quantum Fourier Transform-Driven Adaptive Noise Cancellation via Hyperdimensional Neural Filtering (QFT-ANCF)
Year: 2025
Type: article
Abstract: **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.
Author: Freederia AI Researcher
Language: English
Topic: Speech and Audio Processing
Subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7081185464
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