Title :
Fast subspace tracking by a novel information criterion
Author :
Miao, Yongfeng ; Hua, Yingbo
Author_Institution :
Dept. of Electr. & Electron. Eng., Melbourne Univ., Parkville, Vic., Australia
Abstract :
A new approach to tracking the principal subspace of a vector sequence is developed. This approach is based on a novel non-quadratic cost function referred to as novel information criterion (NIC). The NIC algorithm is guaranteed to converge globally to an arbitrary set of orthonormal base vectors of the desired principal subspace. It is also a fast algorithm as it has a computational complexity of O(M/sup 2/r) flops per update in a batch mode implementation or O(Mr) flops per update in a recursive least-squares implementation, where M is the vector dimension and r the predetermined dimension of the principal subspace. The NIC algorithm is more general and more robust than the PAST algorithm proposed by Yang (see IEEE Trans. Signal Processing, vol.43, no.1, p.95-107, 1995).
Keywords :
adaptive estimation; array signal processing; computational complexity; convergence of numerical methods; direction-of-arrival estimation; information theory; least squares approximations; tracking; DOA; PAST algorithm; batch mode; computational complexity; convergence rate; fast adaptive subspace estimation; fast algorithm; fast subspace tracking; global convergence; nonquadratic cost function; novel information criterion; orthonormal base vectors; principal subspace; real-time signal processing; recursive least-squares; vector dimension; vector sequence; Computational complexity; Convergence; Cost function; Data compression; Filtering; Least squares methods; Neural networks; Resonance light scattering; Robustness; Sensor arrays;
Conference_Titel :
Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on
Conference_Location :
Pacific Grove, CA, USA
Print_ISBN :
0-8186-8316-3
DOI :
10.1109/ACSSC.1997.679116