Chung P C, Krile T F
Dept. of Electr. Eng., Nat. Cheng Kung Univ., Tainan.
IEEE Trans Neural Netw. 1995;6(2):357-67. doi: 10.1109/72.363471.
The performance capability of quadratic Hebbian type associative memories (QHAM's) in the presence of interconnection faults is examined, and equations for predicting the probability of direct convergence P(dc) given a fraction of interconnection faults are developed. The interconnection faults considered are the equivalent of open circuit and short circuit synaptic interconnections in electronic implementations. Our results show that a network with open circuit interconnection faults has a higher probability of direct convergence P (dc) than a network with short circuit interconnection faults, when the fraction of failed interconnections p is small and the short circuit signal G is large. Certain values of G are found to have only mild effects on network performance degradation. Network reliability characteristics taking the generalization capability into account are also analyzed. All of these results are compared with those of Hebbian type associative memories (HAM's), which have linear association network models. Our results indicate that QHAM's have much higher network capacity and fault tolerance capability in the presence of interconnection faults. However, the fault tolerance to input errors in QHAM's is much less than that of HAM's.
研究了二次Hebbian型联想记忆（QHAM）在存在互连故障时的性能能力，并推导了给定互连故障比例时预测直接收敛概率P(dc)的方程。所考虑的互连故障等同于电子实现中的开路和短路突触互连。我们的结果表明，当故障互连比例p较小且短路信号G较大时，具有开路互连故障的网络比具有短路互连故障的网络具有更高的直接收敛概率P(dc)。发现G的某些值对网络性能下降只有轻微影响。还分析了考虑泛化能力的网络可靠性特征。将所有这些结果与具有线性关联网络模型的Hebbian型联想记忆（HAM）的结果进行了比较。我们的结果表明，QHAM在存在互连故障时具有更高的网络容量和容错能力。然而，QHAM对输入错误的容错能力远低于HAM。
