Improved MEMS Magnetometer Adaptive Filter Noise Reduction and Compensation Method

Ning, Zhiwen; Fu, Jun; Yang, Chan; Lv, Teng

doi:10.1109/jsen.2021.3130652

Cited by 8 publications

(2 citation statements)

References 11 publications

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“…The RMSE is a metric to compare values that the approach predicted with actual values obtained in the modeled environment. This is calculated using equation (7) ( )…”

Section: ) Root Mean Square Error (Rmse)mentioning

confidence: 99%

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Electronic Information System Signal Noise for Noise Reduction using Variational Bayesian based Robust Adaptive Filter

Yongjie Peng

2024

jes

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The most significant issues for a thousand users is the unwanted or loud signals in sound files, it is impossible to eliminate or minimize these noise signals without knowledge their types and ranges. To overcome this issue, present an Electronic Information System Signal Noise for Noise Reduction using Variational Bayesian based Robust Adaptive Filter (EIS-SNR-VBRAF) is proposed. Initially, the data is collected from Adaptive Myriad Filter using Time-Varying Noise and Signal-Dependent Parameters dataset. Then, the data is given for Pre-processing section, Variational Bayesian based Robust Adaptive Filter (VBRAF) is used to reduce the signal noise from Gaussian Noise, Traffic noise and Audio signal back ground noise. The proposed technique is implemented and efficacy of EIS-SNR-VBRAF technique is assessed by support of numerous performances such as BER, Signal-to-Noise-Ratio (SNR), Mean Squared Error, Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error, Structural Similarity Index, Cross-Correlation and Computational Complexity is analyzed. The proposed EIS-SNR-VBRAF method attains 21.18%, 23.52% and 23.65% lower RMSE, 21.52%, 21.76% and 23.24% higher PSNR, 21.19%, 21.73% and 20.48% higher Structural Similarity Index are compared with existing methods like early detection of mechanical malfunctions in vehicles utilizing sound signal processing (ED-MMV-SSP),noise reduction in infrasound signals based on mask coefficient binary weighting generalized cross correlation non-negative matrix factorization algorithm (NRID-MCWG-NMFA) and Click-event sound detection in automotive industry using machine/deep learning (CE-SDSI-DL) respectively.

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“…The RMSE is a metric to compare values that the approach predicted with actual values obtained in the modeled environment. This is calculated using equation (7) ( )…”

Section: ) Root Mean Square Error (Rmse)mentioning

confidence: 99%

“…The type of Gaussian noise is taken into account in this actual noisy environment. The authors came to the conclusion that audio signals with varying ripple factors and frequencies might have their noise levels successfully reduced by using the Butterworth filter [5][6][7]. The order of varying frequencies yields distinct outcomes.…”

Section: Introductionmentioning

confidence: 99%