Comparison of Two Approaches to Modeling Additive White Gaussian Noise as It Acts on Arbitrary Signals

The purpose of this paper is to substantiate the correct method for modeling additive white Gaussian noise under conditions of using analog filtering when processing a signal-noise mixture. To achieve the result, two methods of noise modeling used in signal processing theory for Gaussian channels are considered: the first is a traditional simplified discrete method, and the second is a more complex, but functionally correct analog-discrete method. As a result of the comparison, the undeniable advantages of the analog-discrete method are proven. A conclusion was made about the preference of using the proposed new method, which ensures the complete adequacy of the noise model.

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Publication Details

Journal
International Journal of Communications Network and System Sciences
Published
2025-01-01
DOI
https://doi.org/10.4236/ijcns.2025.184004
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
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article

Comparison of Two Approaches to Modeling Additive White Gaussian Noise as It Acts on Arbitrary Signals

Serhii Rassomakhin, Joseph Brifman
International Journal of Communications Network and System Sciences
Neural Networks and Applications
article

Comparison of Two Approaches to Modeling Additive White Gaussian Noise as It Acts on Arbitrary Signals

Serhii Rassomakhin, Joseph Brifman
article en

Abstract

The purpose of this paper is to substantiate the correct method for modeling additive white Gaussian noise under conditions of using analog filtering when processing a signal-noise mixture. To achieve the result, two methods of noise modeling used in signal processing theory for Gaussian channels are considered: the first is a traditional simplified discrete method, and the second is a more complex, but functionally correct analog-discrete method. As a result of the comparison, the undeniable advantages of the analog-discrete method are proven. A conclusion was made about the preference of using the proposed new method, which ensures the complete adequacy of the noise model.

International Journal of Communications Network and System SciencesVol. 18(04)
Institute of Marine and Coastal Research (AR)
Openalex Percentile: Top 93%
Neural Networks and Applications
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