Name
Abstract | ||
|---|---|---|
The ongoing motor output of the brain depends on its remarkable ability to rapidly transform and fuse a variety of sensory streams in real-time. The brain processes these data using networks of neurons that communicate by asynchronous spikes, a technology that is dramatically different from conventional electronic systems. We report here a step towards constructing electronic systems with analogous performance to the brain. Our VLSI spiking neural network combines in real-time three distinct sources of input data; each is place-encoded on an individual neuronal population that expresses soft Winner-Take-All dynamics. These arrays are combined according to a user-specified function that is embedded in the reciprocal connections between the soft Winner-Take-All populations and an intermediate shared population. The overall network is able to perform function approximation (missing data can be inferred from the available streams) and cue integration (when all input streams are present they enhance one another synergistically). The network performs these tasks with about 80% and 90% reliability, respectively. Our results suggest that with further technical improvement, it may be possible to implement more complex probabilistic models such as Bayesian networks in neuromorphic electronic systems. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/ISCAS.2012.6271788 | 2012 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 2012) |
Keywords | Field | DocType |
bayesian network,real time systems,spiking neural network,bayesian methods,neural nets,probabilistic model,vlsi,function approximation | Population,Random neural network,Computer science,Neuromorphic engineering,Probabilistic neural network,Bayesian network,Artificial intelligence,Spiking neural network,Artificial neural network,Very-large-scale integration | Conference |
ISSN | Citations | PageRank |
0271-4302 | 5 | 0.46 |
References | Authors | |
3 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dane Corneil | 1 | 8 | 0.88 |
| Daniel Sonnleithner | 2 | 10 | 1.44 |
| Emre Neftci | 3 | 183 | 17.52 |
| Elisabetta Chicca | 4 | 584 | 49.28 |
| Matthew Cook | 5 | 142 | 11.78 |
| Giacomo Indiveri | 6 | 1460 | 148.21 |
| Rodney J. Douglas | 7 | 593 | 242.90 |