Implementing spiking neural networks for real-time signal-processing and control applications: A model-validated FPGA approach

Pearson, Martin; Pipe, Anthony G.; Melhuish, Chris; Mitchinson, B.; Nibouche, Mokhtar; Gurney, K.; Gilhespy, I.

doi:10.1109/TNN.2007.891203

All Outputs (2)

Audio Localization for Robots Using Parallel Cerebellar Models (2018)
Journal Article
Baxendale, M., Pearson, M., Nibouche, M., Secco, E., & Pipe, T. (2018). Audio Localization for Robots Using Parallel Cerebellar Models. IEEE Robotics and Automation Letters, 3(4), 3185-3192. https://doi.org/10.1109/LRA.2018.2850447

© 2016 IEEE. A robot audio localization system is presented that combines the outputs of multiple adaptive filter models of the Cerebellum to calibrate a robot's audio map for various acoustic environments. The system is inspired by the MOdular Selec... Read More about Audio Localization for Robots Using Parallel Cerebellar Models.

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.