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Benchmark Network II
Garibaldi Pineda-Garcia edited this page May 11, 2016
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Input type: Poisson spikes (NE15-Poissonian)
Network:
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Spiking Deep Belief Network (DBN)
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One input layer network
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Two hidden layers (500 neurons each)
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Fully connected decision layer (10 neurons)
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Current based LIF-exp neurons:
Parameter Values Units Tau_m 5 s Tau_refrac 2 ms V_reset 0 mV V_rest 0 mV V_thresh 1 mV
Training:
- Off-line training
- Unsupervised standard Contrastive Divergence for first layers
- Decision layer is trained with supervision
- Siegert approximation as the activation function
Testing:
- 1.5 kHz input rate
- Weights are just transferred to the spiking network
Performance:
- 94.94% accuracy
- 16ms latency
- 1.88M Sopbs
Hardware Platform | Accuracy (%) | Sim Time (s) | Enery (KJ) | Ref |
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SpiNNaker | 94.94 | 10, 000 | 2.97 |