Sliding window orthonormal past algorithm

R. Badeau; K. Abed-Meraim; G. Richard; B. David

Sliding window orthonormal past algorithm

R. Badeau
, K. Abed-Meraim
, G. Richard
, B. David

Telecom Paris

Résultats de recherche: Contribution à un journal › Article de conférence › Revue par des pairs

Résumé

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.

langue originale	Anglais
Pages (de - à)	261-264
Nombre de pages	4
journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	5
état	Publié - 1 janv. 2003
Evénement	2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong-Kong Durée: 6 avr. 2003 → 10 avr. 2003

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title = "Sliding window orthonormal past algorithm",

abstract = "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.",

author = "R. Badeau and K. Abed-Meraim and G. Richard and B. David",

year = "2003",

month = jan,

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AU - Badeau, R.

AU - Abed-Meraim, K.

AU - Richard, G.

AU - David, B.

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N2 - 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.

AB - 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.

UR - https://www.scopus.com/pages/publications/0141855371

M3 - Conference article

AN - SCOPUS:0141855371

SN - 1520-6149

VL - 5

SP - 261

EP - 264

JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

T2 - 2003 IEEE International Conference on Accoustics, Speech, and Signal Processing

Y2 - 6 April 2003 through 10 April 2003

ER -

Sliding window orthonormal past algorithm

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