Matrix analysis
Adaptive filter theory
The SVD and reduced rank signal processing
Signal Processing - Theme issue on singular value decomposition
Matrix computations (3rd ed.)
Parallel Optimization: Theory, Algorithms and Applications
Parallel Optimization: Theory, Algorithms and Applications
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Convex Optimization
IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
Reduced-rank adaptive filtering using Krylov subspace
EURASIP Journal on Applied Signal Processing
EURASIP Journal on Applied Signal Processing
Linear Estimation and Detection in Krylov Subspaces
Linear Estimation and Detection in Krylov Subspaces
Krylov-proportionate adaptive filtering techniques not limited to sparse systems
IEEE Transactions on Signal Processing
Reduced-rank adaptive filtering
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
IEEE Transactions on Signal Processing
Analysis of conjugate gradient algorithms for adaptive filtering
IEEE Transactions on Signal Processing
An efficient robust adaptive filtering algorithm based on parallelsubgradient projection techniques
IEEE Transactions on Signal Processing
Online Kernel-Based Classification Using Adaptive Projection Algorithms
IEEE Transactions on Signal Processing - Part I
Adaptive Parallel Quadratic-Metric Projection Algorithms
IEEE Transactions on Audio, Speech, and Language Processing
IEEE Transactions on Audio, Speech, and Language Processing
Blind multiuser detection: a subspace approach
IEEE Transactions on Information Theory
A multistage representation of the Wiener filter based on orthogonal projections
IEEE Transactions on Information Theory
Performance of reduced-rank linear interference suppression
IEEE Transactions on Information Theory
On the equivalence of three reduced rank linear estimators with applications to DS-CDMA
IEEE Transactions on Information Theory
Adaptive maximum SINR RAKE filtering for DS-CDMA multipath fading channels
IEEE Journal on Selected Areas in Communications
Blind adaptive reduced-rank detection for DS-CDMA signals in multipath channels
IEEE Journal on Selected Areas in Communications
Hi-index | 35.68 |
In this paper, we propose a novel reduced-rank adaptive filtering algorithm exploiting the Krylov subspace associated with estimates of certain statistics of input and output signals. We point out that, when the estimated statistics are erroneous (e.g., due to sudden changes of environments), the existing Krylov-subspace-based reduced-rank methods compute the point that minimizes a "wrong" mean-square error (MSE) in the subspace. The proposed algorithm exploits the set-theoretic adaptive filtering framework for tracking efficiently the optimal point in the sense of minimizing the "true" MSE in the subspace. Therefore, compared with the existing methods, the proposed algorithm is more suited to adaptive filtering applications. A convergence analysis of the algorithm is performed by extending the adaptive projected subgradient method (APSM). Numerical examples demonstrate that the proposed algorithm enjoys better tracking performance than the existing methods for system identification problems.