Recovering faulty self-organizing neural networks: by weight shifting technique
C. Khunasaraphan, Thitipong Tanprasert, Chidchanok Lursinsap · 2002
A fault tolerant technique of feedforward neural networks, called weight shifting, and its analytical models are proposed. The technique is applied to recover a self-organized network when some faulty links and/or neurons occur during the operation. If some input links of a specific neuron are detected faulty, their weights will be shifted to healthy links of the same neuron. On the other hand, if a faulty neuron is encountered, then we can treat it as a special case of faulty links by considering all the output links of that neuron to be faulty. The aim of this technique is to recover the network in a short time without any retraining and hardware repair.>