Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Explorations in parallel distributed processing: a handbook of models, programs, and exercises
Using and designing massively parallel computers for artificial neural networks
Journal of Parallel and Distributed Computing - Special issue on neural computing on massively parallel processing
Neural network implementation using reconfigurable architectures
Selected papers from the Oxford 1993 international workshop on field programmable logic and applications on More FPGAs
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The need for high precision calculations in various scientific disciplines has led to development of systems with various solutions specific to the problem on hand. The complexity of such systems not withstanding, a generic solution could be the use of neural networks. To be able to leverage the best out of the neural network, hardware implementations are ideal as they give speed-up of several orders of magnitude over software simulations. A simple architecture for such a neuro-chip is proposed in this paper. The neuro-chip supports the current draft version of the IEEE-754 standard for floating-point arithmetic. The synthesis results indicate an estimated 84 MCUPS speed of operation.