Blind Source Separation: A Comparative Study of Classical Statistical Methods and Deep Learning Architectures Article Swipe
This master's project investigates Blind Source Separation (BSS), a signal processing problem aimed at extracting individual source signals from mixed observations without prior knowledge. The report presents a detailed study of both classical techniques, such as PCA and ICA, and modern deep learning approaches, including TasNet and DPRNN-TasNet, highlighting their improvements in handling linear and non-linear mixtures. It also explores BSS applications across audio, biomedical, telecommunications, finance, and image processing, demonstrating how the integration of traditional and deep learning methods advances the accuracy and efficiency of source separation in complex, real-world scenarios.
Related Topics
Concepts
Deep learning
Blind signal separation
Artificial intelligence
Computer science
Signal processing
Machine learning
Source separation
Pattern recognition (psychology)
Deep neural networks
Deep belief network
Image processing
Artificial neural network
Statistical model
SIGNAL (programming language)
Linear model
Open source
Data modeling
Data source
Separation (statistics)
Feature extraction
Metadata
- Type
- article
- Landing Page
- https://doi.org/10.5281/zenodo.17879956
- OA Status
- green
- OpenAlex ID
- https://openalex.org/W7114774302
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W7114774302Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.5281/zenodo.17879956Digital Object Identifier
- Title
-
Blind Source Separation: A Comparative Study of Classical Statistical Methods and Deep Learning ArchitecturesWork title
- Type
-
articleOpenAlex work type
- Publication year
-
2025Year of publication
- Publication date
-
2025-12-10Full publication date if available
- Authors
-
Bennani, NizarList of authors in order
- Landing page
-
https://doi.org/10.5281/zenodo.17879956Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.5281/zenodo.17879956Direct OA link when available
- Concepts
-
Deep learning, Blind signal separation, Artificial intelligence, Computer science, Signal processing, Machine learning, Source separation, Pattern recognition (psychology), Deep neural networks, Deep belief network, Image processing, Artificial neural network, Statistical model, SIGNAL (programming language), Linear model, Open source, Data modeling, Data source, Separation (statistics), Feature extractionTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
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