Título: Nonlinear Independent Component Analysis: Theoretical Review And Applications
Autores: Simas Filho, E. F.; Seixas, J. M.
Resumo: This paper reviews the Nonlinear Independent Components Analysis and its applications to blind source separation. An overview of the main statistical principles that guide the search for the independent components is formulated. The uniqueness of solution and some algorithms for estimating the nonlinear independent components are discussed. Experimental results using a synthetic database are used for performance comparison. A practical application in experimental high-energy physics is also presented.
Palavras-chave: Nonlinear ICA; Neural Networks; Blind Source Separation; Nonlinear Mixtures; Signal Detection
Páginas: 22
Código DOI: 10.21528/lmln-vol5-no2-art3
Artigo em PDF: vol5-no2-art3.pdf
Arquivo BibTex: vol5-no2-art3.bib