Name
Abstract | ||
|---|---|---|
This paper elaborates on a new class of orthonormal power-based algorithms for fast estimation and tracking of the principal or minor subspace of a vector sequence. The proposed algorithms are closely related to the natural power method that has the fastest convergence rate among many power-based methods such as the Oja method, the projection approximation subspace tracking (PAST) method, and the novel information criterion (NIC) method. A common feature of the proposed algorithms is the exact orthonormality of the weight matrix at each iteration. The orthonormality is implemented in a most efficient way. Besides the property of orthonormality, the new algorithms offer, as compared to other power based algorithms, a better numerical stability and a linear computational complexity. |
Year | DOI | Venue |
|---|---|---|
2002 | 10.1023/A:1014445221814 | VLSI Signal Processing |
Keywords | Field | DocType |
adaptive algorithm,orthonormality,principal & minor component analysis,subspace tracking | Subspace topology,Orthonormality,Computer science,Algorithm,Orthonormal basis,Rate of convergence,Adaptive algorithm,Numerical stability,Power iteration,Computational complexity theory | Journal |
Volume | Issue | ISSN |
31 | 1 | 0922-5773 |
Citations | PageRank | References |
8 | 0.57 | 24 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| K. Abed-Meraim | 1 | 1962 | 164.99 |
| A. Chkeif | 2 | 84 | 6.16 |
| Y. Hua | 3 | 209 | 19.58 |
| S. Attallah | 4 | 39 | 3.85 |