Blind knowledge based algorithms based on second order statistics

L. Perros-Meilhac; P. Duhamel; P. Chevalier; E. Moulines

doi:10.1109/icassp.1999.761369

Blind knowledge based algorithms based on second order statistics

L. Perros-Meilhac
, P. Duhamel
, P. Chevalier
, E. Moulines

Telecom Paris

Research output: Contribution to journal › Conference article › peer-review

Abstract

Most second order Single Input Multiple Output (SIMO) identification algorithms identify the global impulse channel response, convolution of an emission filter and a propagation channel. This paper makes an explicit use of this channel structure in a second order algorithm. We present several structured methods exploiting more or less prior informations on the emission filter. Proofs of convergence are provided, and simulations show that some knowledge based algorithms greatly improve over classical blind algorithms, even in the case where the knowledge is partial.

Original language	English
Pages (from-to)	2901-2904
Number of pages	4
Journal	ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume	5
DOIs	https://doi.org/10.1109/icassp.1999.761369
Publication status	Published - 1 Jan 1999
Event	Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-99) - Phoenix, AZ, USA Duration: 15 Mar 1999 → 19 Mar 1999

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10.1109/icassp.1999.761369

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abstract = "Most second order Single Input Multiple Output (SIMO) identification algorithms identify the global impulse channel response, convolution of an emission filter and a propagation channel. This paper makes an explicit use of this channel structure in a second order algorithm. We present several structured methods exploiting more or less prior informations on the emission filter. Proofs of convergence are provided, and simulations show that some knowledge based algorithms greatly improve over classical blind algorithms, even in the case where the knowledge is partial.",

author = "L. Perros-Meilhac and P. Duhamel and P. Chevalier and E. Moulines",

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AU - Perros-Meilhac, L.

AU - Duhamel, P.

AU - Chevalier, P.

AU - Moulines, E.

PY - 1999/1/1

Y1 - 1999/1/1

N2 - Most second order Single Input Multiple Output (SIMO) identification algorithms identify the global impulse channel response, convolution of an emission filter and a propagation channel. This paper makes an explicit use of this channel structure in a second order algorithm. We present several structured methods exploiting more or less prior informations on the emission filter. Proofs of convergence are provided, and simulations show that some knowledge based algorithms greatly improve over classical blind algorithms, even in the case where the knowledge is partial.

AB - Most second order Single Input Multiple Output (SIMO) identification algorithms identify the global impulse channel response, convolution of an emission filter and a propagation channel. This paper makes an explicit use of this channel structure in a second order algorithm. We present several structured methods exploiting more or less prior informations on the emission filter. Proofs of convergence are provided, and simulations show that some knowledge based algorithms greatly improve over classical blind algorithms, even in the case where the knowledge is partial.

U2 - 10.1109/icassp.1999.761369

DO - 10.1109/icassp.1999.761369

M3 - Conference article

AN - SCOPUS:0032634271

SN - 1520-6149

VL - 5

SP - 2901

EP - 2904

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 - Proceedings of the 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP-99)

Y2 - 15 March 1999 through 19 March 1999

ER -

Blind knowledge based algorithms based on second order statistics

Abstract

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