Innovative Applications of Quantum Signal Processing in Network Security and Image Processing

This thorough overview paper investigates how quantum computing could revolutionize communication systems by resolving the intrinsic drawbacks of classical signal processing. Due to the rapid improvements in technology, these systems are subject to increasing demands for larger connection densities and improved spectrum efficiency, which presents substantial hurdles for conventional signal processing. The acceptance and expansion of modern communication technologies are impeded by these obstacles, which are typified by a trade-off between computing complexity and communication performance. Based on quantum mechanics, quantum computing offers a powerful substitute for classical algorithms by introducing a new paradigm that drastically lowers computational complexity for certain applications. This paper explores the history of quantization in classical communication signals and explores the use of quantum computing techniques in critical applications such as data detection, multi-user detection and channel estimation. The work showcases sophisticated methods for image denoising and Fourier transformations, expanding the conversation to include quantum processing of image signals. These quantum methods show significant promise for improving spectral analysis efficiency, reducing noise and increasing processing speed and accuracy. This study offers a thorough basis for future research and technical innovation in the field of image and conventional signal processing by outlining the current state of the art and possible uses of quantum computing in the future.

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Publication Details

Journal
SPIN
Published
2024-10-17
DOI
https://doi.org/10.1142/s201032472440006x
Primary Topic
Spectroscopy Techniques in Biomedical and Chemical Research
Type
article
Field-Weighted Citation Impact
0.00
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article

Innovative Applications of Quantum Signal Processing in Network Security and Image Processing

Jinfeng He, Zelin Wang, Zhengyang Qi, Lin Zhang
SPIN
Spectroscopy Techniques in Biomedical and Chemical Research
article

Innovative Applications of Quantum Signal Processing in Network Security and Image Processing

Jinfeng He, Zelin Wang, Zhengyang Qi, Lin Zhang
article en

Abstract

This thorough overview paper investigates how quantum computing could revolutionize communication systems by resolving the intrinsic drawbacks of classical signal processing. Due to the rapid improvements in technology, these systems are subject to increasing demands for larger connection densities and improved spectrum efficiency, which presents substantial hurdles for conventional signal processing. The acceptance and expansion of modern communication technologies are impeded by these obstacles, which are typified by a trade-off between computing complexity and communication performance. Based on quantum mechanics, quantum computing offers a powerful substitute for classical algorithms by introducing a new paradigm that drastically lowers computational complexity for certain applications. This paper explores the history of quantization in classical communication signals and explores the use of quantum computing techniques in critical applications such as data detection, multi-user detection and channel estimation. The work showcases sophisticated methods for image denoising and Fourier transformations, expanding the conversation to include quantum processing of image signals. These quantum methods show significant promise for improving spectral analysis efficiency, reducing noise and increasing processing speed and accuracy. This study offers a thorough basis for future research and technical innovation in the field of image and conventional signal processing by outlining the current state of the art and possible uses of quantum computing in the future.

SPINVol. 15(02)
Nantong University (CN)
Openalex Percentile: Top 88%
Spectroscopy Techniques in Biomedical and Chemical Research
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Innovative Applications of Quantum Signal Processing in Network Security and Image Processing — Jinfeng He, Zelin Wang, et al. · SPIN (2024) | TGRS Research Map | TGRS