Title :
Global dynamics in principal singular subspace networks
Author :
Elfadel, Ibrahim M.
Author_Institution :
Masimo Corp., Laguna Hills, CA, USA
Abstract :
A left (resp. right) principal singular subspace of dimension p is the subspace spanned by the p left (resp. right) singular vectors corresponding to the p largest singular values of the cross-correlation matrix of two stochastic processes. We study the global dynamics of a system of nonlinear ordinary differential equations (ODEs) that govern the unsupervised Hebbian learning of left and right principal singular subspaces from samples of the two stochastic processes. In particular, we show that these equations admit a simple Lyapunov function when they are restricted to a well defined smooth, compact manifold, and that they are related to a matrix Riccati differential equation. Moreover, we show that in the case p=1, the solutions of these ODEs can be given in closed form
Keywords :
Hebbian learning; Lyapunov matrix equations; correlation methods; nonlinear differential equations; signal sampling; stochastic processes; Lyapunov function; closed form solution; cross-correlation matrix; global dynamics; largest singular values; matrix Riccati differential equation; nonlinear ordinary differential equations; principal singular subspace networks; samples; singular vectors; smooth compact manifold; stochastic processes; unsupervised Hebbian learning; Adaptive control; Differential equations; Intelligent networks; Matrix decomposition; Nonlinear dynamical systems; Riccati equations; Signal processing algorithms; Stochastic processes; Strontium; Symmetric matrices;
Conference_Titel :
Acoustics, Speech, and Signal Processing, 1995. ICASSP-95., 1995 International Conference on
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2431-5
DOI :
10.1109/ICASSP.1995.479708