TY - GEN
T1 - Realization of fault tolerance for spiking neural networks with particle swarm optimization
AU - Feng, Ruibin
AU - Leung, Chi-Sing
AU - Tsang, Peter
PY - 2015
Y1 - 2015
N2 - The spiking neural network (SNN) model has been an important topic in the past two decades. Many training algorithms, such as SpikeProp, were designed and applied to various applications. However, the fault tolerant ability in SNNs was not fully understood. Based on our study, the SNN model with the classical training objective function cannot even handle the single fault situation, in which one of the hidden neurons is damage. To improve the fault tolerant ability, we design an objective function and utilize the particle swarm optimization approach to minimize it. Simulation results show that our approach is much better than the classical objective function. © Springer International Publishing Switzerland 2015
AB - The spiking neural network (SNN) model has been an important topic in the past two decades. Many training algorithms, such as SpikeProp, were designed and applied to various applications. However, the fault tolerant ability in SNNs was not fully understood. Based on our study, the SNN model with the classical training objective function cannot even handle the single fault situation, in which one of the hidden neurons is damage. To improve the fault tolerant ability, we design an objective function and utilize the particle swarm optimization approach to minimize it. Simulation results show that our approach is much better than the classical objective function. © Springer International Publishing Switzerland 2015
KW - Fault tolerance
KW - Particle swarm optimization
KW - Spiking neural networks
UR - http://www.scopus.com/inward/record.url?scp=84951854613&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-84951854613&origin=recordpage
U2 - 10.1007/978-3-319-26535-3_10
DO - 10.1007/978-3-319-26535-3_10
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9783319265346
VL - Part II
T3 - Lecture Notes in Computer Science
SP - 79
EP - 86
BT - Neural Information Processing
A2 - Sabri Arik, null
A2 - Tingwen Huang, null
A2 - Weng Kin Lai, null
A2 - Qingshan Liu, null
PB - Springer
CY - Cham
T2 - 22nd International Conference on Neural Information Processing (ICONIP 2015)
Y2 - 9 November 2015 through 12 November 2015
ER -