Chung P C, Krile T F
Dept. of Electr. Eng., Texas Tech. Univ., Lubbock, TX.
IEEE Trans Neural Netw. 1992;3(6):969-80. doi: 10.1109/72.165598.
The performance of Hebbian-type associative memories (HAMs) in the presence of faulty (open- and short-circuit) synaptic interconnections is examined and equations for predicting network reliability are developed. The results show that a network with open-circuit interconnection faults has a higher probability of direct convergence than a network with short-circuit interconnection faults when the fraction of failed interconnections is small and the short-circuit signal is large. The results are extended to the case where network attraction radius is considered. Under certain assumptions, it is found that the expected numbers of neurons with b, b-1, b-2,. . .,1 input error bits in their state update are equal. Because of the capability of error correction, an asynchronous HAM is also found to have a higher probability of direct convergence than a synchronous HAM. Using these results, network reliability and generalization capability can be estimated when both the interconnection faults and the number of error bits in the probe vectors are taken into account.
研究了在存在故障（开路和短路）突触互连的情况下赫布型联想记忆（HAM）的性能，并推导了预测网络可靠性的方程。结果表明，当故障互连的比例较小时且短路信号较大时，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。研究结果扩展到考虑网络吸引半径的情况。在某些假设下，发现状态更新中具有b、b - 1、b - 2、...、1个输入错误比特的神经元的预期数量相等。由于具有纠错能力，还发现异步HAM比同步HAM具有更高的直接收敛概率。利用这些结果，当同时考虑互连故障和探测向量中的错误比特数量时，可以估计网络的可靠性和泛化能力。
