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Absorption of echo signal for underwater acoustic signal target system using hybrid of ensemble empirical mode with machine learning techniques

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Abstract

Underwater acoustic sensor signal processing relies on sound absorption of underwater acoustic energy. Echo absorption of underwater acoustic waves is a challenging area because of the complexity of a marine ecosystem and the uniqueness of an underwater acoustic route. We developed Improved Weighed Quantum Particle Swarm Optimization-based Ensembles Empirical Mode Decomposition (IWQPSO-EEMD), Mean Square Variance (MSV), & Least Mean Squares Algorithm (LMSA) driven echoes absorbing underwater acoustic waves to address the problem. Initially, the original data was divided into Intrinsic Mode Functions (IMF) separated into noise IMFs and actual IMFs. Next, noise IMFs detected the echo elements and removed them using MSV and LMSA. The final denoised sensor signal was received after reconstructing both genuine and removed noise IMFs. Lastly, we employ a fusion approach that surpasses the Blind Source Separator & Categorization method. Examine simulation sounds with actual underwater sound waves compared to many other echo absorption methods. We demonstrate the validity of the IWQPSO-EEMD-MSV-LMSA with superior echo absorption efficiency and real application potential.

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Authors and Affiliations

  1. Department of Computer Science and Engineering, Sri Sai Ram Institute of Technology, Anna University , Chennai, India

    P. Ashok

  2. Department of Computer Science and Engineering, Sri Sairam Engineering College, Chennai, India

    B. Latha

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  1. P. Ashok
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  2. B. Latha
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Correspondence to P. Ashok.

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Ashok, P., Latha, B. Absorption of echo signal for underwater acoustic signal target system using hybrid of ensemble empirical mode with machine learning techniques. Multimed Tools Appl 82, 47291–47311 (2023). https://doi.org/10.1007/s11042-023-15543-2

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  • DOI: https://doi.org/10.1007/s11042-023-15543-2

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