Tracking non-stationary dynamical system phase using multi-map and temporal self-organizing architecture

Khouzam Bassem 1 Hervé Frezza-Buet 1
1 IMS - Equipe Information, Multimodalité et Signal
UMI2958 - Georgia Tech - CNRS [Metz], SUPELEC-Campus Metz
Abstract : This paper presents a multi-map recurrent neural architecture, exhibiting self-organization to deal with the partial observations of the phase of some dynamical system. The architecture captures the dynamics of the system by building up a representation of its phases, coping with ambiguity when distinct phases provide identical observations. The architecture updates the resulted representation to adapt to changes in its dynamics due to self-organization property. Experiments illustrate the dynamics of the architecture when fulfilling this goal.
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Khouzam Bassem, Hervé Frezza-Buet. Tracking non-stationary dynamical system phase using multi-map and temporal self-organizing architecture. NaBIC 2011, Oct 2011, Salamanca, Spain. pp.163-168, ⟨10.1109/NaBIC.2011.6089453⟩. ⟨hal-00652312⟩

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