Implementing spiking neural networks for real-time signal-processing and control applications: A model-validated FPGA approach
(2007)
Journal Article
Pearson, M., Pipe, A. G., Mitchinson, B., Gurney, K., Melhuish, C., Gilhespy, I., & Nibouche, M. (2007). Implementing spiking neural networks for real-time signal-processing and control applications: A model-validated FPGA approach. IEEE Transactions on Neural Networks, 18(5), 1472-1487. https://doi.org/10.1109/TNN.2007.891203
In this paper, we present two versions of a hardware processing architecture for modeling large networks of leaky-integrate-and-fire (LIF) neurons; the second version provides performance enhancing features relative to the first. Both versions of the... Read More about Implementing spiking neural networks for real-time signal-processing and control applications: A model-validated FPGA approach.