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A parallel and modular multi-sieving neural network architecture with multiple control networks

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2 Author(s)
Bao-Liang Lu ; RIKEN, Inst. of Phys. & Chem. Res., Nagoya, Japan ; Ito, K.

We have proposed a constructive learning method, called multi-sieving learning, for implementing automatic decomposition of learning tasks and a parallel and modular multi-sieving network architecture in our previous work (1995). In this paper we present a new parallel and modular multi-sieving neural network architecture to which multiple control networks are introduced. In this architecture the learning task for a control network is decomposed into a finite set of manageable subtasks, and each subtask is learned by an individual control sub-network. An important advantage of this architecture is that the learning tasks for control networks can be learned efficiently, and therefore automatic decomposition of complex learning tasks can be achieved easily

Published in:

Systems, Man, and Cybernetics, 1996., IEEE International Conference on  (Volume:2 )

Date of Conference:

14-17 Oct 1996