Digital wireless audio signal noise reduction optimization method based on Matlab

Through the digital wireless audio signal noise reduction optimization method based on Matlab, the SVM-LSTM model is used to process real-time transmission data and noise feature databases, which solves the problem of poor adaptability of the existing technology in complex noise environments, and achieves efficient noise reduction and signal quality improvement.

CN119694331AActive Publication Date: 2025-03-25SHENZHEN LEZHIYUAN TECHNOLOGY CO LTD
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Patent Information

Application Number
CN202411868598.6
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2024-12-18
Publication Date
2025-03-25
Estimated Expiration
2044-12-18

AI Technical Summary

Technical Problem

The existing digital wireless audio signal noise reduction technology is poorly adaptable in complex and variable noise environments, making it difficult to achieve comprehensive noise filtering, and is easy to introduce additional noise to cause signal distortion, resulting in unsatisfactory noise reduction effect.

Method used

The digital wireless audio signal noise reduction optimization method based on Matlab is adopted, and noise recognition and feature analysis is performed by obtaining real-time transmission data, a noise feature database is established, and a noise reduction model is constructed using the SVM-LSTM model to achieve effective processing of complex noise environments.

Benefits of technology

While maintaining low latency, it realizes effective noise reduction for complex and variable noise environments, improves the accuracy and processing efficiency of noise recognition, reduces signal distortion, and significantly improves the quality of audio signals.

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Abstract

The invention relates to the technical field of digital signal processing, in particular to a digital wireless audio signal noise reduction optimization method based on Matlab, and the method comprises the steps: S1, obtaining the real-time transmission data of a digital wireless audio signal; s2, performing noise identification processing according to the real-time transmission data of the digital wireless audio signal to obtain noise type data of the digital wireless audio signal; s3, performing feature analysis processing based on Matlab according to the real-time transmission data and the noise type data of the digital wireless audio signal to establish a noise feature database of the digital wireless audio signal; s4, establishing a noise reduction model of the digital wireless audio signal based on SVM-LSTM by using the real-time transmission data of the digital wireless audio signal and the noise feature database; s5, utilizing the noise reduction model of the digital wireless audio signal to obtain a noise reduction optimization result of the digital wireless audio signal; compared with the prior art, the limitation of the existing filtering noise reduction technology is solved, and the noise reduction accuracy and processing efficiency are improved.
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