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Erschienen in:
2006 | OriginalPaper | Buchkapitel
A Virtual Machine for Neural Computers
verfasst von : João Pedro Neto
Erschienen in: Artificial Neural Networks – ICANN 2006
Verlag: Springer Berlin Heidelberg
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Neural Networks are mainly seen as algorithmic solutions for optimization and learning tasks where the ability to spread the acquired knowledge into several neurons, i.e., the use of sub-symbolic computation, is the key. We have shown in previous works that neural networks can perform other types of computation, namely symbolic and chaotic computations. Here in, we show how these nets can be decomposed into tuples which can be efficient calculated by software or hardware simpler than previous neural solutions.