An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation

التفاصيل البيبلوغرافية
العنوان: An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation
المؤلفون: Sprekeler, Dr. Henning, Zito, Tiziano, Wiskott, Dr. Laurenz
المصدر: Sprekeler, Dr. Henning and Zito, Tiziano and Wiskott, Dr. Laurenz (2010) An Extension of Slow Feature Analysis for Nonlinear Blind Source Separation. [Preprint]
Publication Status: Preprint
سنة النشر: 2010
مصطلحات موضوعية: Computer Science: Machine Learning, Machine Learning
الوصف: We present and test an extension of slow feature analysis as a novel approach to nonlinear blind source separation. The algorithm relies on temporal correlations and iteratively reconstructs a set of statistically independent sources from arbitrary nonlinear instantaneous mixtures. Simulations show that it is able to invert a complicated nonlinear mixture of two audio signals with a reliability of more than $90$\%. The algorithm is based on a mathematical analysis of slow feature analysis for the case of input data that are generated from statistically independent sources.
نوع الوثيقة: Journal Article
وصف الملف: application/pdf
URL الوصول: http://cogprints.org/7056/
رقم الانضمام: edscog.7056
قاعدة البيانات: CogPrints