AN STDP TRAINING ALGORITHM FOR A SPIKING NEURAL NETWORK WITH DYNAMIC THRESHOLD NEURONS

作者：Strain T J; McDaid L J^*; McGinnity T M; Maguire L P; Sayers H M

来源：International Journal of Neural Systems, 2010, 20(6): 463-480.

DOI：10.1142/S0129065710002553

• STDP
• supervised learning
• dynamic threshold neurons
• SNNs

This paper proposes a supervised training algorithm for Spiking Neural Networks (SNNs) which modifies the Spike Timing Dependent Plasticity (STDP) learning rule to support both local and network level training with multiple synaptic connections and axonal delays. The training algorithm applies the rule to two and three layer SNNs, and is benchmarked using the Iris and Wisconsin Breast Cancer (WBC) data sets. The effectiveness of hidden layer dynamic threshold neurons is also investigated and results are presented.

• 出版日期2010-12