Optimal performance of second-order multidimensional ICA

Dana Lahat, Jean Francois Cardoso, Hagit Messer

פרסום מחקרי: פרסום בכתב עתמאמר מכנסביקורת עמיתים

תקציר

Independent component analysis (ICA) and blind source separation (BSS) deal with extracting mutually-independent elements from their observed mixtures. In "classical" ICA, each component is one- dimensional in the sense that it is proportional to a column of the mixing matrix. However, this paper considers a more general setup, of multidimensional components. In terms of the underlying sources, this means that the source covariance matrix is block-diagonal rather than diagonal, so that sources belonging to the same block are correlated whereas sources belonging to different blocks are uncorrelated. These two points of view -correlated sources vs. multidimensional components- are considered in this paper. The latter offers the benefit of providing a unique decomposition. We present a novel, closed-form expression for the optimal performance of second-order ICA in the case of multidimensional elements. Our analysis is verified through numerical experiments.

שפה מקוריתאנגלית
עמודים (מ-עד)50-57
מספר עמודים8
כתב עתLecture Notes in Computer Science
כרך5441
מזהי עצם דיגיטלי (DOIs)
סטטוס פרסוםפורסם - 2009
פורסם באופן חיצוניכן
אירוע8th International Conference on Independent Component Analysis and Signal Separation, ICA 2009 - Paraty, ברזיל
משך הזמן: 15 מרץ 200918 מרץ 2009

טביעת אצבע

להלן מוצגים תחומי המחקר של הפרסום 'Optimal performance of second-order multidimensional ICA'. יחד הם יוצרים טביעת אצבע ייחודית.

פורמט ציטוט ביבליוגרפי