How to multiply matrices faster
How to multiply matrices faster
Analog computation via neural networks
Theoretical Computer Science
Learning in neural networks: VLSI implementation strategies
Fuzzy logic and neural network handbook
Neural networks and analog computation: beyond the Turing limit
Neural networks and analog computation: beyond the Turing limit
Parallelization of algorithms with recurrent neural networks
ICANNGA'11 Proceedings of the 10th international conference on Adaptive and natural computing algorithms - Volume Part I
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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.