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              <p>L'application des méthodes d'analyse de données à des séries temporelles se trouve vite limitée par le nombre souvent très élevé des observations composant les séries. Ce travail propose une nouvelle technique de réduction de la dimension temporelle d'une série multivariée préservant la structure de variance-covariance, élément de base pour de nombreuses méthodes d'analyse de données. Cette nouvelle technique est fondée sur l'extraction des principales tendances locales composant la série et permet la conservation de la dimension temporelle des séries réduites. Les résultats de cette approche sont illustrés sur une application médicale en anesthésie-réanimation.</p>
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