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Blind Source Separation Using Block-coordinate Relative Newton Method.pdf

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Preview of Blind source separation using block-coordinate relative Newton method
🔗 Source: vista.cs.technion.ac.il
📊 Size: 1.57 MB
👤 Author: Administrator
⬇️ Downloads: 95

Summary

Blind source separation using block-coordinate relative Newton method is presented, generalizing the relative Newton method for quasi-maximum likelihood blind source separation. The Hessian matrix's special structure allows block-coordinate Newton descent, reducing computational complexity and boosting performance. Simulations on artificial and real data show superior separation quality compared to other accepted blind source separation methods. The method is particularly effective for sparse or sparsely representable sources, where the absolute value function or its smooth approximation is used. The block-coordinate relative Newton method is compared to the original modified relative Newton algorithm and other state-of-the-art methods, demonstrating faster convergence and better performance.

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Description

Blind source separation using block-coordinate relative Newton method is presented, generalizing the relative Newton method for quasi-maximum likelihood blind...

Technical Information

  • File Format: PDF
  • File Size: 1.57 MB
  • Pages: 21
  • Language: EN
  • Author: Administrator
  • Total Downloads: 95
  • Last Updated: 5 days ago

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This PDF document about Blind source separation using block-coordinate relative Newton method provides comprehensive information and guidance. Whether you're a beginner or advanced user, this resource offers valuable insights into Blind source separation using block-coordinate relative Newton method.

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Blind guideBlind tutorialsource guidesource tutorialseparation guideseparation tutorialusing guideusing tutorialblock-coordinate guideblock-coordinate tutorialrelative guiderelative tutorialNewton guideNewton tutorialmethod guidemethod tutorial

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