A parallel approach for backpropagation learning of neural networks.

From: Journal of Computer Science & Technology | Date: March 1, 1999| Author: Piccoli F., Crespo, M.; Gallard R., Prinsta M. | Copyright information

ABSTRACT

Fast response, storage efficiency, fault tolerance and graceful degradation in face of scarce or spurious inputs make neural networks appropriate tools for Intelligent Computer Systems. But on the other hand, learning algorithms for neural networks involve CPU intensive processing and consequently great effort has been done to develop parallel implementations intended for a reduction of learning time.

Looking at both sides of the coin, this paper show...

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