2011 · 13 citations · 8 references
EngineeringComputer EngineeringComputer SystemsField-programmable Gate ArraysReconfigurable ComputingSystem-on-chip DesignConfigurable Logic BlocksField-programmable Gate Array ArchitectureFpga ArchitectureNeural CircuitsNeural Signal ProcessingSpiking Neural NetworksDigital Signal Processing BlocksLeaky Integrate-and-fire ModelsNeuromorphic HardwareSpike-based Signal ProcessingSpiking ActivitySpiking Network ArchitecturesSpiking Neural Network ModelsSpiking Neuron Models
A field programmable gate array (FPGA) implementation of a hardware spiking neural network is presented. The system is able to realize different signal processing tasks using the synchronization of oscillatory leaky integrate and fire neurons. The use of a bit slice architecture and short, local interconnections make it adaptable to projects of various scales. The system is also designed to efficiently process groups of synchronized neurons. A fully connected network of 648 neurons and 419904 synapses is implemented on a stand-alone Xilinx XC5VSX50T FPGA, processing up to 6M spikes/s. We describe the resource usage for the whole system as well as for each functional block, and illustrate the functioning of the circuit on a simple image recognition task.
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Dmitri B. Strukov, Gregory S. Snider, Duncan R. Stewart et al. · Nature · 2008 · 11.5K citations
Engineering, Electrical Engineering, Electronic Materials +5
A model for visual shape recognition.
Peter M. Milner · Psychological Review · 1974 · 603 citations
Image Segmentation Based on Oscillatory Correlation
DeLiang Wang, David Terman · Neural Computation · 1997 · 310 citations
Challenges for large-scale implementations of spiking neural networks on FPGAs
Liam Maguire, T.M. McGinnity, Brendan Glackin et al. · Neurocomputing · 2007 · 179 citations