A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae Search
Currently, the widely used blind source separation algorithm is typically associated with issues such as a sluggish rate of convergence and unstable accuracy, and it is mostly suitable for the separation of independent source signals. Nevertheless, source signals are not always independent of one an...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-10-01
|
| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/19/8325 |
| _version_ | 1797575167820431360 |
|---|---|
| author | Mingyang Tang Yafeng Wu |
| author_facet | Mingyang Tang Yafeng Wu |
| author_sort | Mingyang Tang |
| collection | DOAJ |
| description | Currently, the widely used blind source separation algorithm is typically associated with issues such as a sluggish rate of convergence and unstable accuracy, and it is mostly suitable for the separation of independent source signals. Nevertheless, source signals are not always independent of one another in practical applications. This paper suggests a blind source separation algorithm based on the bounded component analysis of the enhanced Beetle Antennae Search algorithm (BAS). Firstly, the restrictive assumptions of the bounded component analysis method are more relaxed and do not require the signal sources to be independent of each other, broadening the applicability of this blind source separation algorithm. Second, the objective function of bounded component analysis is optimized using the improved Beetle Antennae Search optimization algorithm. A step decay factor is introduced to ensure that the beetle does not miss the optimal point when approaching the target, improving the optimization accuracy. At the same time, since only one beetle is required, the optimization speed is also improved. Finally, simulation experiments show that the algorithm can effectively separate independent and dependent source signals and can be applied to blind source separation of images. Compared to traditional blind source separation algorithms, it has stronger universality and has faster convergence speed and higher accuracy compared to the original independent component analysis algorithm. |
| first_indexed | 2024-03-10T21:34:49Z |
| format | Article |
| id | doaj.art-8e08d01a4f8c4c0685da8c4b93e3076f |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T21:34:49Z |
| publishDate | 2023-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-8e08d01a4f8c4c0685da8c4b93e3076f2023-11-19T15:05:57ZengMDPI AGSensors1424-82202023-10-012319832510.3390/s23198325A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae SearchMingyang Tang0Yafeng Wu1College of Energy and Power, Northwestern Polytechnical University, Xi’an 710129, ChinaCollege of Energy and Power, Northwestern Polytechnical University, Xi’an 710129, ChinaCurrently, the widely used blind source separation algorithm is typically associated with issues such as a sluggish rate of convergence and unstable accuracy, and it is mostly suitable for the separation of independent source signals. Nevertheless, source signals are not always independent of one another in practical applications. This paper suggests a blind source separation algorithm based on the bounded component analysis of the enhanced Beetle Antennae Search algorithm (BAS). Firstly, the restrictive assumptions of the bounded component analysis method are more relaxed and do not require the signal sources to be independent of each other, broadening the applicability of this blind source separation algorithm. Second, the objective function of bounded component analysis is optimized using the improved Beetle Antennae Search optimization algorithm. A step decay factor is introduced to ensure that the beetle does not miss the optimal point when approaching the target, improving the optimization accuracy. At the same time, since only one beetle is required, the optimization speed is also improved. Finally, simulation experiments show that the algorithm can effectively separate independent and dependent source signals and can be applied to blind source separation of images. Compared to traditional blind source separation algorithms, it has stronger universality and has faster convergence speed and higher accuracy compared to the original independent component analysis algorithm.https://www.mdpi.com/1424-8220/23/19/8325blind source separationbounded component analysisBeetle Antennae Search |
| spellingShingle | Mingyang Tang Yafeng Wu A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae Search Sensors blind source separation bounded component analysis Beetle Antennae Search |
| title | A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae Search |
| title_full | A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae Search |
| title_fullStr | A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae Search |
| title_full_unstemmed | A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae Search |
| title_short | A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae Search |
| title_sort | blind source separation method based on bounded component analysis optimized by the improved beetle antennae search |
| topic | blind source separation bounded component analysis Beetle Antennae Search |
| url | https://www.mdpi.com/1424-8220/23/19/8325 |
| work_keys_str_mv | AT mingyangtang ablindsourceseparationmethodbasedonboundedcomponentanalysisoptimizedbytheimprovedbeetleantennaesearch AT yafengwu ablindsourceseparationmethodbasedonboundedcomponentanalysisoptimizedbytheimprovedbeetleantennaesearch AT mingyangtang blindsourceseparationmethodbasedonboundedcomponentanalysisoptimizedbytheimprovedbeetleantennaesearch AT yafengwu blindsourceseparationmethodbasedonboundedcomponentanalysisoptimizedbytheimprovedbeetleantennaesearch |