Spiking neural networks (SNN) are biological more plausible models that use spikes as the means of temporal and spatial coding of information. The problem arises in that large numbers of these neurons communicating in parallel with real time requirements are necessary for cutting edge sensory applications. This requires that new hardware or software techniques have to be developed. Here a novel codesign is presented incorporating the benefits of state-of-the-art field programmable gate array (FPGA) technology aided with a software system employing a visual data flow environment to create a rapid flexible platform for the simulation and implementation of SNN.
|Title of host publication||Unknown Host Publication|
|Number of pages||6|
|Publication status||Published - Sep 2003|
|Event||IEEE Cybernetics Intelligence - Challenges and Advances (CICA) 2003 - Reading, UK|
Duration: 1 Sep 2003 → …
|Conference||IEEE Cybernetics Intelligence - Challenges and Advances (CICA) 2003|
|Period||1/09/03 → …|
Johnston, S., Prasad, G., Maguire, LP., McGinnity, TM., & Wu, Q. (2003). A Design Flow for the Hardware Implementation of Spiking Neural Networks onto FPGAs. In Unknown Host Publication (pp. 124-129). IEEE.