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Transmission of Multiple Signals through an Optical Fiber Using Wavefront Shaping

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Comprehensive Separation Algorithm for Single-Channel Signals Based on Symplectic Geometry Mode Decomposition.

Xinyu Wang¹, Jin Zhao¹, Xianliang Wu¹

¹Key Lab of Intelligent Computing & Signal Processing, Ministry of Education, Anhui University, Hefei 230601, China.

Sensors (Basel, Switzerland)

|January 23, 2024

Summary

This summary is machine-generated.

This study introduces SGMD-FastICA, a novel algorithm for separating single-channel mixed signals. It effectively overcomes noise interference and FastICA limitations for improved signal separation.

Keywords:

FastICA SGMD Symplectic Geometry Component signal separation

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Area of Science:

Signal Processing
Data Analysis

Background:

Extracting source signals from complex mixtures is challenging.
FastICA struggles with single-channel signals and noisy environments.

Purpose of the Study:

To propose a comprehensive single-channel mixed signal separation algorithm.
To address limitations of existing methods in noisy conditions.

Main Methods:

Combined Symplectic Geometry Mode Decomposition (SGMD) and FastICA.
SGMD decomposes signals; Pearson correlation selects components.
Virtual multi-channel signals created for FastICA input.

Main Results:

SGMD effectively eliminates noise while preserving signal integrity.
SGMD-FastICA demonstrates superior separation compared to EMD-FastICA and VMD-FastICA.
The algorithm enables direct separation of single-channel signals.

Conclusions:

The proposed SGMD-FastICA algorithm enhances single-channel signal separation.
It offers a robust solution for noisy environments, improving upon FastICA.
This method provides a significant advancement in mixed signal decomposition.