HOS based distinctive features for preliminary signal classification

Maciej Pȩdzisz; Ali Mansour

HOS based distinctive features for preliminary signal classification

Maciej Pȩdzisz
, Ali Mansour

ENSTA

ENSTA Bretagne

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

2 Citations (Scopus)

Résumé

We consider the problem of preliminary classification of digitally modulated signals. The goal is to simplify further signal analysis (synchronization, signal separation, modulation identification and parameters estimation) by making initial separation among the most known classes of signals. Proposed methodology is mainly based on Higher Order Statistics (HOS) of the distributions of instantaneous amplitude and frequency. The experimental results emphasize the performance of the proposed set of features.

langue originale	Anglais
Pages (de - à)	1158-1164
Nombre de pages	7
journal	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	3195
état	Publié - 1 déc. 2004

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title = "HOS based distinctive features for preliminary signal classification",

abstract = "We consider the problem of preliminary classification of digitally modulated signals. The goal is to simplify further signal analysis (synchronization, signal separation, modulation identification and parameters estimation) by making initial separation among the most known classes of signals. Proposed methodology is mainly based on Higher Order Statistics (HOS) of the distributions of instantaneous amplitude and frequency. The experimental results emphasize the performance of the proposed set of features.",

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T1 - HOS based distinctive features for preliminary signal classification

AU - Pȩdzisz, Maciej

AU - Mansour, Ali

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N2 - We consider the problem of preliminary classification of digitally modulated signals. The goal is to simplify further signal analysis (synchronization, signal separation, modulation identification and parameters estimation) by making initial separation among the most known classes of signals. Proposed methodology is mainly based on Higher Order Statistics (HOS) of the distributions of instantaneous amplitude and frequency. The experimental results emphasize the performance of the proposed set of features.

AB - We consider the problem of preliminary classification of digitally modulated signals. The goal is to simplify further signal analysis (synchronization, signal separation, modulation identification and parameters estimation) by making initial separation among the most known classes of signals. Proposed methodology is mainly based on Higher Order Statistics (HOS) of the distributions of instantaneous amplitude and frequency. The experimental results emphasize the performance of the proposed set of features.

UR - https://www.scopus.com/pages/publications/35048848503

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AN - SCOPUS:35048848503

SN - 0302-9743

VL - 3195

SP - 1158

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JO - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

JF - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

ER -

HOS based distinctive features for preliminary signal classification

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