2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). · 2004 · 16 citations · 11 references
ComputingComputer ScienceAlgorithmsOptimizationTime Series AnalysisDigital Signal ProcessingSignal ProcessingSmall-signal AnalysisState EstimationTime Series ComputationTracking SystemsComplexityConvergenceGlobal Convergence AnalysisSliding Window AlgorithmsSliding WindowsSparse TrackingSubspace IdentificationSubspace Learning
This paper introduces an orthonormal version of the sliding-window projection approximation subspace tracker (PAST). The new algorithm guarantees the orthonormality of the signal subspace basis at each iteration. Moreover, it has the same complexity as the original PAST algorithm, and like the more computationally demanding natural power (NP) method, it satisfies a global convergence property, and reaches an excellent tracking performance.
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Projection approximation subspace tracking
Bin Yang · IEEE Transactions on Signal Processing · 1995 · 1.3K citations
Fast orthonormal PAST algorithm
Karim Abed‐Meraim, A. Chkeif, Yingbo Hua · IEEE Signal Processing Letters · 2000 · 198 citations