Multi-winners self-organizing episodic associative memory

We propose an episodic associative memory (EAM) called multi-winners self-organizing EAM (MWS-EAM) which can represent analog scenes of an episode distributedly and can recall the next scene from the distributed representation. The proposed MWS-EAM represents any scene of an episode into the representation layer distributedly, and then stores the relation of the scenes with its representation and the representation with next scene into the bottom up weights and the top down weights, respectively. The trained proposed MWS-EAM can recall all of the scenes in the stored episode by receiving only one scene