基于RBF网络的神经控制在FPGA上实现

S. Brassai, L. Bakó, G. Pana, S. Dan
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引用次数: 13

摘要

RBF径向基函数网络是专门用于硬件实现的,这种类型的网络在机器人和控制领域得到了成功的应用,在这些领域,网络的实时能力是特别重要的。在FPGA上实现神经网络有几个优点,重点是并行性和实时性。本文讨论了RBF型神经网络的硬件实现,硬件实现的神经处理器的结构、参数和功能模块。
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Neural control based on RBF network implemented on FPGA
The RBF radial basis function network is intended especially for hardware implementation and this type of network is used successfully in the areas of robotics and control, where the real time capabilities of the network are of particular importance. The implementation of neural networks on FPGA has several benefits, with emphasis on parallelism and the real time capabilities. This paper discusses the hardware implementation of the RBF type neural network, the architecture and parameters and the functional modules of the hardware implemented neuro-processor.
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