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The paper presents a distributed approach for the classification and selection of the interesting epileptic signals based on a dynamical vectorial analysis method. The objective is to limit the instantaneous workload by avoiding redundant computations and ensuring a better distribution of the load. Our approach deals with the information recorded during the intracerebral exploration and it exploits...
This work is focused on the study of the organization of the SEEG signals during epileptic seizures with multi-agent system approach. This approach is based on cooperative mechanisms of auto-organization at the micro level and of emergence of a global function at the macro level. In order to evaluate this approach we propose a distributed collaborative approach for the classification of the interesting...
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